Luís and João Batalha: Fermat's Library and the Art of Studying Papers | Lex Fridman Podcast #209

the following is a conversation with. luiz and joao batala. brothers and co-founders of firma's. library which is an incredible platform. for annotating papers as they write on. the formats library website justice. pierre de fermat scribbled his famous. last theorem in the margins professional. scientists academics and citizen. scientists can annotate equations. figures ideas and write in the margins. for mars library is also a really good. twitter account to follow i highly.

recommend it they post little visual. factoids and explorations that reveal. the beauty of mathematics. i love it. quick mention of our sponsors. skiff. simply safe indeed netsuite and for. sigmatic check them out in the. description to support this podcast as a. side note let me say a few words about. the dissemination of scientific ideas. i believe that all scientific articles. should be freely accessible to the.

public. they currently are not. in one analysis i saw more than 70 of. published research articles are behind a. paywall. in case you don't know the funders of. the research whether that's government. or industry. aren't the ones putting up the paywall. the journals are the ones putting up the. paywall while using unpaid labor from. researchers for the peer review process. where is all that money from the paywall. going. in this digital age the costs here.

should be minimal. this cost can easily be covered through. donation advertisement or public funding. of science. the benefit versus the cost of all. papers being free to read is obvious and. the fact that they're not free goes. against everything science should stand. for which is the free dissemination of. ideas that educate and inspire. science cannot be a gated institution. the more people can freely learn and. collaborate on ideas the more problems. we can solve in the world together and.

the faster we can drive old ideas out. and bring new. better ideas in. science is beautiful and powerful and. its dissemination in this digital age. should be free. this is the lex friedman podcast and. here's my conversation with luiz and. joao batala. luis you suggested an interesting idea. imagine if most papers had a. backstory section the same way that they.

have an abstract. so. knowing more about how the authors ended. up working on a paper can be extremely. insightful and then you went on to give. a backstory for the feynman qed paper. this is all in a tweet by the way we're. doing tweet analysis today. how much of the human backstory do you. think is important in understanding. the idea itself that's presented in the. paper or in general. i think this gives way more context to. the work of of scientists i think people. a lot of people have this almost kind of.

romantic misconception that. the way a lot of scientists work is. almost as the sum of eureka moments. where all of a sudden they sit down and. start writing two papers in a row and. the papers are usually isolated and when. you actually look at it it's the papers. are you know chapters of a way more. complex uh story. and the definement qed paper is a good. example so feynman was actually going. through a pretty dark phase before. writing that paper it was he lost.

enthusiasm with physics and doing. physics problems and there was one time. when he was in the cafeteria of cornell. and he saw a guy that was throwing. flights in the air and he noticed that. there was when the plate was in the air. there were two movements there the plate. was wobbling but he also noticed that. the the cornell symbol was rotating and. he was able to figure out the equations. of motions uh the equations of motions. of those uh plates and that uh led him. to kind of think a little bit about.

electron orbits in relativity which led. to the paper of. about quantum electrodynamics so that. kind of reignited. his interest in physics and and and. ended up publishing the paper that led. to the his nobel prize basically and i. think it's it's. there are a lot of really interesting. backstories about papers that readers. never get to know friends we did a. couple of months ago um. an ama around a paper a pretty famous.

paper the gans paper with ian goodfellow. and so we did an ama where everyone was. could ask questions about the paper and. ian was responding to those questions. you also he was also telling the story. of how he got the idea for that paper in. a bar so there was also an interesting. and a back story i also read a book by. cedric villani. uh these cedric velani is this. mathematician the fields medalist and in.

his book he tries to explain how he got. from like. a phd student to the fields metal and he. tries to be as descriptive as possible. every single step how we got to the. fields metal and it's interesting also. to see just the amount of random. interactions and discussions with other. researchers sometimes over coffee and. how it led to like. fundamental breakthroughs and some of. his most important papers so i think. it's super interesting to have that. context of of the backstory well the ian. goodfellow story is kind of interesting.

and perhaps that's true for feynman as. well i don't know if it's romanticizing. the thing but. it seems like just. a few little insights and a little bit. of work. does most of the leap required. do you have a sense that for a lot of. the stuff you've looked at. just looking back through history. uh it it wasn't necessarily the grind. of like andrew wiles of the females last. theorem for example. it was more like a a brilliant moment of. insight in fact ian goodfellow has a.

kind of sadness to him almost in that. at that time in machine learning like at. that time especially in uh. for gans. you could. code something up really quickly on a. single machine. and almost do the invention go from idea. to uh experimental validation and like a. single night a single person could do it. and now there's kind of a sadness that a. lot of the breakthroughs you might have. in machine learning kind of require. large-scale experiments. so it was almost like the early days.

so i wonder how many. low-hanging fruit there are in science. and mathematics. and even engineering where it's like. you could do that little experiment. quickly like you have an insight and a. bar why is it always a bar but you have. an insight at a bar and then just. implement. and the world changes. it's it's a good point i think it also. depends a lot on the maturity of the. field when you look at a field like. mathematics like it's a pretty mature.

field uh feels like machine learning um. it's it's growing pretty fast. and um it's actually pretty pretty. interesting i i looked up like the. number of. new papers. on archive with the keyword machine. learning and like 50 of those papers. have been published on in the last 12. months so you can see just the same zero. five zero fifty percent so you can see. the the the the magnitude of growth in. that field and so i think like as fields.

mature like those types of moments i. think naturally. uh are less frequent um. it's just a consequence of. that the other point that is interesting. about the backstory is that it can. really make it more memorable in a way. and and by making it more memorable it's. it kind of sediments the knowledge more. in your mind i remember also reading the. sort of the backstory to. to dijkstra's shortest path algorithm. right where he came up with it uh.

essentially while he was. sitting down at a at a coffee shop in. amsterdam and he and he came up with. that algorithm over 20 minutes and one. interesting aspect is he didn't have any. pen or paper at the time and so he had. to do it all in his mind and so. there's only so much complexity that you. can handle if you're just thinking about. it in your mind and that like when you. think about the simplicity of dijkstra's. shortest path finding algorithm it's you. know knowing that backstory helps. sediment that algorithm in your mind so.

that you don't forget about it as easily. it might be from you that i saw. a meme about texture. it's like he's trying to solve it he. comes up with some kind of random path. and then it's like my parents aren't. home and then he does uh. he figures out the algorithm for the. shortest path. i strike through words to convey memes. but that's hilarious i don't know if. it's in post that we construct stories. that romanticize it apparently with.

newton there was no apple. especially when you're working on. problems that have a physical. manifestation or a visual manifestation. it feels like the world. could be an inspiration to you. so it doesn't have to be completely in. on paper. like you could be sitting at a bar and. all of a sudden see something and a. pattern will. will spark another pattern and you can. visualize it and rethink a problem in a. particular way.

of course you can also load the math. that you have on paper and always carry. that with you so when you show up to the. bar some little inspiration could be the. thing that changes it is there any other. people. almost on the human side whether it's. physics with feynman. derock einstein or computer science. touring anybody else any backstories. that you remember that jump out. because i'm also referring to. not necessarily these stories where. something magical happens. but these are personalities they have.

big egos some of them are super friendly. some of them are like self-obsessed some. of them have anger issues some of them. how do i describe feynman but he appears. to uh. have a. appreciation of the beautiful in all its. forms it has a wit and a cleverness and. a humor about him so it does that come. into play in terms of the construction. of the science. well i think you brought up newton. newton is it's a good example also to. think about his backstory because you.

know there's a certain backstory of. newton that people always talk about but. then there's a whole. another aspect of him. that is also a big part of the person. that he was but you know he was really. into alchemy right and that he spent a. lot of time. thinking about that and writing about it. and he took it very seriously he was. really into bible interpretation and. trying to predict things based on the. bible and so there's also a whole. backstory then and of course you need to. look at it in the context that and the.

time that when newton lived um but a but. it adds to his personality and it's. important to also understand those. aspects then maybe. you know uh i'm not people people are. not as proud to teach to little kids. but it's important it was part of who he. was and and maybe without those he who. knows what he would have done otherwise. so. well the the cool thing about alchemy. i don't know how it was viewed at the. time. but it almost like to me symbolizes.

dreaming of the impossible. like most of the breakthrough ideas kind. of seem impossible until they're. actually done it's like achieving human. flight it's not completely obvious to me. that alchemy is impossible or like. putting myself in the mindset of the. time. and perhaps even still. every everything that uh. you know some of the most incredible. breakthroughs are. would seem impossible. and i wonder the value of.

believing. almost like focusing and dreaming of the. impossible such that it is actually is. possible in your mind and that in itself. manifests. whether the accomplishing that goal or. making progress in some unexpected. direction so alchemy almost symbolizes. that for me i distinctly remember having. the same thought of thinking you know. when i learned about atoms and that they. have protons and electrons i was like. okay to make gold you just take whatever. has an atomic weight below it and then. shove another proton in there and then.

you have a bunch of gold so like why. don't people do that. it seemed like conceptually is like you. know this sounds feasible you might be. able to do it and you can actually it's. just very very expensive yeah yeah. exactly exactly so in a sense we do have. alchemy and. maybe even back then it wasn't as crazy. that he was so into it. but good people just don't like to talk. about that as much. yeah but newton in general is a very. interesting fellow. anybody else come to mind. in terms of.

people that inspire you. in terms of people that you just. are happy that they have once or still. exist on this earth. i think i mean freeman dyson for me. yeah freeman dyson was was. i've had a chance to actually exchange a. couple of emails with him it was. probably one of the most humble. scientists that i've ever met and that. had a a big impact on me we were trying. we're actually trying to convince him to. annotate a paper on fermat's library.

and i sent him an email asking him. if you could annotate a paper and his. response was something like i have very. limited knowledge i just know a couple. of things about certain fields i'm not. sure if i'm qualified to do that that. was his first response and. and this was someone that should have. won an opera fry's and worked on a bunch. of different fields um did some really. really. great work. and then just the interactions that i. had with him every time i asked him a.

couple of questions about his papers and. uh he always responded saying i'm not. here to answer your questions i just. want to open it more questions. um and uh so that had a big impact on me. it was like just. an example of an extremely humble. yet. accomplished. uh scientist and feynman was also a big. big inspiration in the sense that he was. able to be. you know again extremely talented and. and scientists but at the same time.

socially he was able to to he was also. really smart from a social perspective. and he was able to. interact with people it was also a. really good. teacher and was also to did a awesome. work in terms of um. explaining physics to to the masses and. motivating and getting people interested. in physics. and that for me was was also a big. inspiration. yeah i like the childlike curiosity of. some of those folks like you mentioned. freeman i have daniel kahneman i got a.

chance to meet and interact with. some some of these truly special. scientists. what makes them special is that even in. uh older age. they're still. like there's still that fire of. childlike curiosity that burns. and uh some of that is like not taking. yourself so seriously that you think. you've figured it all out. but almost like thinking that you don't. know much of it. and. that's like step one in having a great.

conversation or collaboration or. exploring a scientific question it's. cool how the very thing that probably. earned people the nobel prize or. or work that's seminal in some way. is the very thing that still burns even. after. uh they've won the prize it's cool to. see and they're rare humans. it seems and to that point i remember. like the last email that i sent to. freeman dyson was like in his last. birthday he was really into number. theory and primes so what i did is i.

took like a photo of him a picture and. then i turned that into like. a giant prime number. so i converted the picture into a bunch. of one and eight and then i moved some. numbers around until it was a prime. um and then i sent him that. also the the visual like it still looked. like the picture it's made up of a. problem that's tricky to do it's hard to. do it looks harder than it actually is. so the the way you do it is like you. convert the darker regions into eights.

and the lighter regions in ones. and then there's just keep flipping yeah. but there's like some primality tests. that are cheaper from a computational. standpoint yes but what it tells you is. it excludes numbers that are not prime. then you end up with a set of numbers. that you don't know if they are prime or. not and then you run the full primality. test on that so you just have to keep. iterating on that and it was it was it's. it's funny because when he got the. picture he was like how did you do that. it was super curious too and then we got.

into the details and again this was he. was already 90 i think 92 or something. and that curiosity was still there um. so you could really see that in in some. of these scientists. so could we talk about vermont's library. yeah absolutely what. is it. what's the main goal what's the dream. it is a platform for annotating papers. in its essence right and so academic. papers can be one of the densest forms. of content out there and generally.

pretty hard to understand at times and. the idea is that you can make them more. accessible and easier to understand by. adding these rich annotations to the. site right and so we can just imagine a. pdf view on your browser and then you. have annotations on each side and then. when you click on them a sidebar expands. and then you have. annotations that support latex and. markdown. and so the idea is that you can. say explain a tougher part of a paper. where there's a step that is not.

completely obvious. or you can add more context to it. and then over time papers can become. easier and. easier to understand and can evolve in a. way but it really came from. myself luige and two other friends we've. been. we've had this this long-running habit. of kind of running a journal club. amongst us we come from different. backgrounds right i studied cs we. studied physics and so we read papers. and present them to each other and uh. and then we tried to bring some of that.

online and that's that's that's when we. decided to to to build fermat's library. um. then over time it kind of. grew into into something uh with with a. broader goal uh. and really what we're trying to do is. trying to help. uh move science in the in the the right. direction. that's really the ultimate goal and and. where we want to take it now so there's. a lot to be said so first of all for. people who haven't seen it.

the interface is exceptionally well done. that's like execution is really. important here absolutely the other. things just to mention. for. a large number of people apparently. which is new to me don't know what latex. is. so it's spelled like latex so be careful. googling it if you haven't before. uh it's uh. uh. sorry i don't even know the correct. terminology type setting it's a. typesetting language. where it's you're basically program.

writing a program that then generates. something that looks. from a typography perspective beautiful. absolutely and uh so a lot of academics. use it to write papers i i think there's. like a bunch of communities that use it. to write papers i would say it's. mathematics physics computer science. yeah that's yeah that's the because i'm. collaborating currently on a paper with. uh two neuroscientists from stanford and. they don't know what.

so i'm using uh microsoft word and uh. mendeley. and like all of those kinds of things. and it's. and i'm being very zen like about about. the whole process but it's fascinating. it's a little heartbreaking actually. because uh. it actually it's it's funny to say but. uh and we'll talk about open science. actually the bigger mission behind for. mars libraries like. really opening up the world of science. to everybody. is these silly.

two facts of like one community uses. latex and another uses word. is actually a barrier between them. that's like it's like boring and. practical in a sense but it makes it. very difficult to collaborate. just on that like i think there if there. are some people that should have. received like a nobel prize that but. we'll never get it and i think one of. those is like donald knuth because of. tech and latex and then. because it had a huge impact in terms of. like just.

making it easier for uh researchers to. put their content out there like making. it uniform as much as possible oh you. mean like a nobel peace prize well maybe. maybe a couple of peace prizes. maybe a nobel peace prize yeah. i. i think so i mean he at a very young age. got the touring award for his work in. algorithms and so on so yeah like an. incredible yeah like when i i think it's. in. it might be even the 60s but i think. it's the 70s that so when he was really. young and then he went on to do like.

incredible work. with his book and uh yeah with tech that. people don't know and and going back. just one. on the reason why we we ended up because. i think this is interesting the reason. why we ended up using the name for mars. library this was because of uh vermont's. last theorem and from us livestream is. actually a funny story like so pierre de. fermat he was like a lawyer and he. wrote like on a book. that he had a solution to fermat's last. theorem which um but that didn't fit the.

margin of that book. and so fermat's lie stream basically. states that there's no solution if you. have uh. integers a b and c there's no solution. to a to the power of n plus b to the. power of n equals to c to the power of. n. if n is bigger than two so there's. there's there's no solutions and. he said that. and. that problem remained open for almost. 300 years i believe and a lot of the.

most famous mathematicians tried to. tackle that problem no one was able to. figure that that out until andrea wiles. uh i think was in in the 90s was able to. publish the solution which was i i. believe almost 300 pages long. and so it's kind of an anecdote that you. know there's a lot of of knowledge and. insights that can be trapped. in the margins then you and there's a. lot of potential energy that you can. release if you actually um spend some. time trying to digest.

that and that was the the the origin. story for. for the name yes you can share the. contents of the margins with the world. exactly that could inspire a solution or. a communication that then leads to a. solution but and and if you think about. papers like papers are as as jean was. saying probably one of the densest. pieces of text that. any human can read and you have these. researchers like some of the brightest. minds in in these fields working on like. new discoveries and publishing these. work on journals that are imposing them.

restrictions in terms of the number of. pages that they can have to explain a. new scientific breakthrough so at the. end of the day papers are not optimized. for clarity and for a proper explanation. of of that content because there are so. many restrictions so there's as i. mentioned there's a lot of potential. energy that can be freed if you actually. try to digest a lot of the contents of. papers. can you explain some of the other things. so margins librarian journal club.

so journal club is what a lot of people. know us for uh where we every week we. release an annotated paper and in all. sorts of different fields with physics. cs math. margins is kind of the same software. that we use to to run the journal club. and to host the annotations but we've. made that available for free to anybody. that wants to use it and so. folks use it at universities and. and. for running journal clubs. and and so we just made that freely.

available and then librarian is a. browser extension that we developed that. is sort of an overlay on top of archive. so it's about bringing some of the same. functionality around comments plus. adding some extra. niceties to to archive like being able. to very easily extract the references of. a paper that you're looking at or being. able to extract the bibtex in order to. cite that paper yourself. so it's an overlay on top of archive the. idea is that you can have that. commenting interface without having to.

leave archive it's kind of incredible i. didn't know about it. and once i've learned of it. it's like holy shit. why isn't it more popular given how. popular archive is like everybody should. be using it archive sucks. or uh let me rephrase that it's limited. yeah in terms of what's interesting. archive is a pretty incredible project. right and it is in in a way it's. it you know it the growth has been.

completely linear over time if you look. at like number of papers published on. archive like you know it's just been. it's pretty much a straight line for the. past 20 years especially for you know. like if you're coming from a startup. background and then you were trying to. do archive you'd probably try like all. sorts of growth acts and like try to. to then maybe like have paid features. and things like that and that would kind. of maybe ruin it and so there's. there's a subtle balance there yeah and. i don't know what what aspects you can. change about it and yeah for some tools.

in science it just takes time for them. to to grow archive is just turned 30 i. believe yeah and for for people that. don't know archive is these kind of. online repository where people put. preprints which are versions of the. papers before they actually make it to. journals. a-r-x-i-v exactly for people who don't. know and it's actually a really vibrant. place to publish your papers in in the. aforementioned. uh communities of mathematics exactly in.

computer science it started with. mathematics and physics and then over. the the last 30 years it evolved and now. actually computer computer science now. it's it's a more popular category than. than physics and math on archive and. there's also which i don't know very. much about like a. biology medical version of that bio. archive yeah by archive um it's recent. it's um it's interesting because if you. look at like these um platforms for. preprints they are. they actually play a super important. role because.

if you look at a category like math. for some papers in math it might take. close to three years. after you click upload paper on the. journal website and the paper gets. published on the website of the journal. so this is literally the longest. upload period on the internet. um and during those three years like. it's it's you know. their content is just you know locked. and so this that's why it's so important. for people to have websites like archive.

so that you can share that before it. goes to the journal with the rest of the. world there was actually on archive that. uh perumann published the the three. pipers that led to the proof of the. poincare conject conjecture and then you. have other fields like. machine learning for instance where the. the field is evolving at such a high. rate that people don't even wait before. the papers go to journals before they. start working on top of those papers so. they publish them on archive then other. people see them they start working on.

that and archive did a really good job. at like building that core platform to. host papers but i i think there's a. really really big opportunity in. building more features on top of that. platform apart from just hosting paper. so collaboration annotations and. like having other things apart from from. papers like code um. and and other things because uh in the. field like machine learning there's a. really big you know as i mentioned. people start working on on top of. preprints and they are assuming that.

that. that preprint is correct. but you really need a way for instance. to maybe. it's not peer review but. distinguish what is good work from bad. work on archive how do you do that so. like a commenting interface like. librarian it's useful for that so that. you can distinguish that um at. in the field that is growing so fast as. machine learning and um and then you. have. platforms that focus for instance on. just biology bioarchive is a good. example um.

bioarchive is also super interesting. because there there's actually. an interesting experiment that was run. in the 60s so in the 60s the nih um. supported this pro this. this experiment called the information. exchange group. which at the time was a way for. researchers to share biology preprints. via mail or using libraries and that. project in the 1960s got cancelled six. years after it started and it was due to.

intense pressure from the journals to. kill that project because they they were. fearing a competition from from the. uh. for in for the journal industry creek uh. was also uh was one of the famous. scientists that opposed. to to the uh information exchange group. and it's interesting because right now. if you analyze the number of biology. papers that. appear first as preprints it's only two. percent of the papers.

and it this was almost 50 almost 50. years after that first experiment so you. can see like that pressure from the. journals to cancel that uh initial. version of a pre-print repo had a. tremendous impact on on on the number of. papers that are showing up in biology as. preprints so it delayed a lot that. that revolution and um. but now platforms like bioarchive are. doing that work but there's still a lot. of room for growth there and i think. it's super important because those are. the papers that are open that everyone.

can read. okay so but if we just look at the. entire process of science as a big. system can we just talk about how it can. be revolutionized. so. you have an idea. uh depending on the field you want to. make that idea concrete you want to run. a few experiments in computer science. there might be some code. there'd be a data set. for you know some of the more sort of. biology. psychology. you might be collecting the data set.

that's called you know a study right. so that's part of that that's part of. the methodology and so you are putting. all that into a paper form. and then. you have some results. and then you you submit that to a place. for. review through the peer review process. and there's a process where how would. you summarize the peer review process. but it's it's really just like a handful. of people look over your paper and. comment and based on that decide whether.

your paper is good or not. so there's a whole broken nature to it. at the same time i love the peer review. process when i buy stuff on amazon. like uh. for like uh the commenting system. whatever that is so okay so there's a. bunch of possibilities for revolutions. there and then there's the other side. which is the collaborative aspect of the. science which is people annotating. people commenting sort of the low effort. collaboration which is a comment.

sometimes as you've talked about a. comment can change everything but you. know or a higher effort collaboration. like more like maybe annotations or even. like contributing to the paper you can. think of like. a. collaborative updating of the paper over. time. so there's all these possibilities for. doing things. better than they've been done. can we talk about some ideas in this. space some ideas that you're working on.

some ideas that uh you're not yet. working on but should be revolutionized. because it does seem. that archive and like open review for. example. are like the craigslist of science like. like. yeah okay i'm very grateful that we have. it but it just feels like. it's like 10 to 20 years like it doesn't. feel like that's a feature the. simplicity of it is a feature it feels. like it's a it's a bug. [Music].

but then again the the pushback there is. uh wikipedia has the same kind of. simplicity to it. and it seems to work exceptionally well. in the crowdsourcing aspect of it i'm. sorry this there's a bunch of stuff. going on on the table let's just pick. random things that we can talk about. wikipedia you know for me it's the. cosmological constant of the internet. it's like i think we are lucky to live. in the parallel universe where wikipedia. exists yes because if if someone had.

pitched me wikipedia like a publicly. edited. encyclopedia like a couple of years ago. like it would be i don't know how many. people would have said that that would. have. survived. yeah i mean it makes almost no sense. it's like having a google doc that. everybody on the internet can edit and. like that will be like the most reliable. source for for knowledge and i don't. know how many but hundreds of thousands. of topics yeah exactly. it's insane it's insane and like you. have and then you have users like. there's one a single user that edited.

one third of the articles on wikipedia. so you have these really really big. power users there are a substantial part. of like what makes wikipedia. successful and so. like. no one would have ever imagined that. that could happen. um and so that that's that's one thing i. i completely agree with what you just. said i also started to interrupt briefly. maybe let's inject that into the. discussion of everything else.

i also believe i've seen that with stack. overflow that one individual or a small. collection of individuals contribute or. revolutionize. most of the community like if you create. a really powerful system for archive. or like open review it made it really. easy. and compelling. and exciting for one person who isn't. like a 10x contributor to do their thing. that's going to change everything it. seems like that was the mechanism that. changed everything for wikipedia and.

that's the mechanism that changed. everything for stack overflow is. gamifying or making it exciting or just. making it fun or pleasant or fulfilling. in some way for those people who are. insane. enough to like answer thousands of. questions or. write thousands of factoids and like. research them and check them all those. kinds of things or read thousands of. papers yeah no stack overflow is another. great example of that and it's just. and and those are both to.

incredibly productive communities that. generate a ton of value and and and. capture almost none of it right and it's. and you know in a way it's almost like. counter um. it's very counter-intuitive that that. that people that these communities would. exist and thrive um. and and it's really hard to. you there aren't that many communities. like that so how do we do that for. science do you have ideas there like.

what are the biggest problems that you. see you're working on some of them. like just on that there are a couple of. really interesting experiments that. people are running an example would be. like the polymath projects so this is a. so kind of a social experiment that was. uh created by tim gowers. fields fields medalist and his idea was. to try to prove that is it possible to. do mathematics in a massively. collaborative collaborative way on the. internet so we decided to pick a couple.

of problems and. test that and they found out that it it. actually it is possible for a specific. types of problems. namely problems that you're able to. break down in in little pieces and go. step by step you might need as as with. open source you might need people that. are just kind of reorganizing the the. house every once in a while and then you. know people throw a bunch of ideas and. then you know you make some progress. then you reorganize you reframe the. problem you go step by step but they.

were actually able to prove that it is. possible to to. uh collaborate online and and. do progress in terms of mathematics um. and so i'm i'm confident that there are. other avenues that could be explored. here can we talk about peer review for. example absolutely i i think like in in. terms of the peer review i think we it's. it's important to look at the bigger. picture here of like. of what this scientific the scientific. publishing ecosystem looks like because.

for me. there there are a lot of things that are. wrong about that entire process so. if you look at for instance at the what. publishing means in like a traditional. journal you have uh journals that pay um. authors. for their articles and then they might. pay like reviewers to um review those. articles and finally they pay. people to um or distributors to. distribute the content. in in the scientific publishing world.

you have scientists that are usually. backed by government grants they are. giving away their work for free in the. form of papers. and then you have other scientists that. are reviewing their work. this process is known as the peer review. process again for free. and then finally we have um. government-backed universities and. libraries that are buying back. all those. all that work so that other scientists. can we can read so this is for me it's.

bizarre you have the government that is. funding the research is paying the. salaries of the scientists it's paying. the salaries of the reviewers and it's. buying back all that uh the product of. their work again. um and i think the problem with this. system and it's what it's why it's so. difficult to to break this. suboptimal equilibrium is because of of. the way academia works right now and the. way you can progress in in your academic. life. and and so. in a lot of fields the the competition.

in academia is is really insane. so you have hundreds of phd students. there are um trying to get to. a professor position and and it's hyper. competitive and the only way for you to. get there. is if you publish papers ideally in. journals with a. high impact factor in computer science. it's all it's often conferences are also. very prestigious or actually more. prestigious than journals now.

so interesting so that's the one. discipline where i mean that has to do. with the thing we've discussed uh in. terms of the how quickly the field turns. around but like uh in eurips cvpr those. conferences are more prestigious or at. the very least as prestigious as the. journal. but doesn't matter the process is what. it is and and and so with the the so for. people that don't know how the impact. factor of a journal is basically the. average number of citations that a paper. would get if it gets published on that. journal.

but so um you can really think that. the problem with the the impact factor. is that it's a way to turn papers into. accounting units. and and and let me unpack this because. it's the impact factor is almost like a. nobility title so because papers are. born with impact even before anyone. reads them so the researchers they don't. have the incentive. to care about if this paper is going to. ever a long-term impact on on on the.

world what they care their goal their. end goal is the paper to get published. yes so that they get that value up front. and so for me that that is one of the. problems of of that and that really. creates a tyranny of of metrics. because at the end of the day if you are. a dean what you want to hire is like. people researchers that publish papers. on journals with high impact factors. because that will increase the ranking. of your university and will allow you to. charge more for tuition so on and so.

forth and um and and that that. especially when you are in super. competitive areas you know that people. will try to gamify that system and and. misconduct starts showing up. um there's a a really interesting book. on this topic called gaming the metrics. it's a book by a researcher called mario. biagioli it goes a lot into like how. these. the impact factor and metrics affect. science negatively and it's interesting.

to think especially in terms of. citations if you look at the early work. of like looking at citations there was a. lot of work that was done by a guy. called eugene garfield and this guy. the early work in terms of citation they. wanted to use they wanted to use. citations as. from a descriptive point of view so what. they wanted to to create was a map. and and that map would create a visual. representation of of influence so. citations would be links. between papers and the ideally what they.

would show they would represent is that. you read someone else's paper and it had. an impact on your research they weren't. supposed to be counted i think this. inspired like larry and sergey's exactly. worked right for google exactly i think. they even mentioned that but what. happens is like as you start counting. citations you create a market. and and the same way like and this was. the the work of eugene garfield was a. big inspiration for larry and sergey for. the pagerank algorithm that um you know. led to the creation of google and they.

even recognize that and and if you think. about it's like the same way there's a. gigantic market for search engine. optimization uh seo where people try to. optimize you know the the page rank and. how i the uh of a web page will rank on. google the same will happen for papers. people will try to optimize like their. site their the impact factors and the. citations that they get and that um. creates a really big problem and if it's. super interesting to actually analyze.

them if you look at the distribution of. the high impact the impact factors of. journals you have like nature with. nature i believe it's like in the low. 40s and then you have i believe science. is high 30s and then you have a really. goo. a good set of good journals that. will. fall between 10 and 30 and then you have. a gigantic tale of of journals that have. impact factor below two and you can. really see two economies here you see. the the.

you know the universities that are maybe. less prestigious less known that where. the faculty are pressured to just. publish papers regardless of the journal. what i want to do is increase the. ranking of my university and so they end. up publishing as many papers as as they. they can in like journals with low. impact factor and unfortunately this is. represents a lot of of the global south. and then you have the luxury good. economy. so for instance for and there are also.

problems here in the luxury good economy. so if you look at the journal like. nature. so with impact factor of like in the low. 40s. there's no way that you're going to be. able to sustain that level of impact. factor by just grabbing the attention of. scientists. what what i mean by that is like. for for the journals the articles that. get published in nature they need to be. new york times great so they need to. make it to the you know to the to the.

big media they need to be captured by. the big media and because that's the. only way for you to capture enough. attention to sustain that level of. citations yes and that of course creates. problems because people then will try to. again gamify the system and have like. titles or abstracts or that are. bigger claim make claims that are bigger. than what is actually can be um. you know sustained by by the data or the. the content of the paper and you'll have. clickbait titles or clickbait abstracts.

and again this is all a consequence of. metrics and uh scientometrics and and. this is a very dangerous cycle that i. think it's very hard to break. but it's happening in academia in a lot. of fields right now. is it fundamentally the existence of. metrics or the metrics just need to be. significantly improved. because uh. like i said the metrics used for amazon. for purchasing. i don't know.

computer parts it's pretty damn good in. terms of selecting which are the good. ones which are not. in that same way if if we had an amazon. type of review system in the space of. ideas in the space of science it feels. like that those metrics would be a. little bit better. sort of when it's um. when it's significantly. more open to the crowd source nature of. the internet. of the of the scientific internet. meaning as opposed to like my biggest.

problem with peer review. has always been. that it's like. five six seven people. usually even less and it's often. nobody's incentivized to do a good job. in the whole process. meaning. it's anonymous. in a way that. doesn't incentivize like doesn't gamify. or incentivize. great work. and also. it doesn't necessarily have to be. anonymous like there has to be um.

the entire system is um. doesn't encourage actual sort of. rigorous review for example like. open review. does kind of incentivize that kind of. process of collaborative review but it's. also imperfect it just feels like. the thing that amazon has which is like. thousands of people contributing their. reviews to a product. it feels like that could be applied to.

science. where. the same kind of thing you're doing with. vermont's library. but doing at a scale that's much larger. it feels like that should be possible. given the number of grad students. given the number of um. general public that get like for example. i. personally as a person. who got an education in mathematics and. computer science like. uh i can i can be a quote-unquote like. reviewer.

on a lot bigger set of things than than. is my exact uh expertise. if i'm one of thousands of reviewers if. i'm the only reviewer or one of five. then i'd better be like an expert in the. thing but if if i uh and i've learned. this with covet which is like. you can just use your basic skills as a. data analyst as a and to contribute to. the review process and a particular. little aspect of a paper and be able to. comment be able to sort of uh.

draw in some references that challenge. the ideas presented or to enrich the. ideas that are presented or you know and. it just feels like crowdsourcing. the review process would be able to. allow you to have. metrics. in terms of how good a paper is that are. much better representative of its actual. impact in the world of its actual value. to the world as opposed to some kind of. arbitrary gamified.

version of its impact. i agree with that i i think we there's. definitely the possibility at least for. more resilient a more resilient system. than what we have today and that's i. think that's kind of what you're. describing alex and and i mean to an. extent we we kind of have like a little. bit of a. heisenberg uncertainty principle when. you pick a metric as soon as you do it. then maybe it works as a good heuristic. for for a short amount of time but soon. enough people would start gamifying and. yeah. but but then you can definitely have.

metrics that are more resilient to. gamification and they'll work as a. better heuristic to to try to push you. in the in. the best direction. but i guess the underlying problem. you're saying is uh there's a shortage. of positions in academia that's a big. problem for me yeah and and that and so. they're going to be constantly gamifying. the metrics it's a bit of a zero-sum. it's very competitive it's what it's a. very competitive field and and that's. what usually happens in very competitive. fields yeah yeah.

but i think some of like the peer review. problems like scale helps i think and. and it's interesting to look at like. what you're mentioning breaking it down. maybe in my smaller parts and having. more people jumping in. um but. th this is definitely a problem and and. the peer review problem as i mentioned. is. is correlated with the problem of like. academic career progression and it's all. intertwined and it's what that's why i. think it's so hard to to break it. um there are like a couple of really.

interesting things that are being done. right now there are a couple of for. instance journals that are overlaid. journals on top of. platforms like archive and bioarchive. that want to remove like the more. traditional journals from the equation. so essentially a journal is just a. collection of links to papers and and um. and what they are trying to do is like. removing that middleman and trying to to. make the review process a little bit. more transparent. um. and and and not charging universities.

like uh there's there's a couple of. there are a couple of more famous um. ones there's one discrete analysis in. mathematics there's one uh called the. quantum journal which we are actually. working with them we have a partnership. with them for the purpose that get. published in quantum journal they also. get the annotations on formats um and. they are doing pretty well they've been. able to grow substantially the problem. there is getting to critical mass so. it's again convincing the researchers. and especially the young researchers. that need. need that impact factor need those.

publications to have citations to not. publish on the traditional journal and. go on an open journal and and publish. their work there there i think there are. a couple of really high-profile. scientists of people like team gowers. that are trying to. incentivize like. famous scientists that already have. tenure and that don't need that to. publish that to increase the reputation. of those journals so that other maybe. younger scientists can start publishing. on on those as well and so they can try. to break that vicious cycle of.

of um the more traditional journals i. mean another possible way to break this. cycle is to. like raise public awareness and just by. force like ban paid journals. like what exactly are they contributing. to the world. like basically making it illegal. to uh. forget the fact that it's mostly. federally funded so that's that's a. super ugly picture too. but like why should knowledge be.

so expensive. like where everyone is working for the. public good. and then there's these gatekeepers. that you know most people can't read. most papers. without having to pay money and. that's that doesn't make any sense. that's like that that should be illegal. i mean that's what you're saying is. exactly right i mean for instance right. i i went to school here in the us we. studied in europe and. you would sit like you'd ask me all the.

time to download papers and send it to. him because he just couldn't get it and. like papers that he needed for his. research and so but he's a student like. he's yeah he's a grad student he was a. grad student but that you know. i'm even referring to just regular. people oh yeah okay that too yeah and i. i think uh during 2020. because of covet a lot of journals put. down the. walls for certain kind of coronavirus or. papers. but like that just gave me an indication. that like.

this should be done for everything it's. it's absurd like people should be. outraged that there's these gates. because. so the moment you dissolve the journals. then there will be an opportunity for. startups. to uh build stuff on top of archive it'd. be an opportunity for like. vermont's library to step up to scale up. to something much even larger i mean. that was the original dream of uh. google which i. always admired which is make the world's.

information accessible actually it's. interesting that google hasn't maybe you. guys can correct me but they uh put. together google scholar which is. incredible. but they and they've did the scanning of. books but they've haven't really. tried to make science accessible. in the in the in the following way like. besides doing google scholar they. haven't like. delved into the papers. right mm-hmm which is especially curious. given what louise was saying right that.

it's kind of in their genesis there's. this. you know research that was very. connected with our papers reference each. other and like building a network out of. that. interesting enough like google but i. think there was a there was not intent. google plus was like the google social. network that got canceled was used by a. lot of researchers yes it was uh whether. i think was just a you know side kind of. a side effect but then a lot of people. ended up migrating to twitter but it was. not on purpose but yeah i agree with you. like they haven't. um gone past the google scholar and well.

you know what that said google's call is. incredible people who are not familiar. it's one of the best. aggregation of all the scientific work. that's out there and especially the. network that connects to all of them. what sites what and also trying to. aggregate all the versions of the papers. that are available there and trying to. merge them in a way that uh one. particular work even though it's. available in a bunch of places counts as. you know like a central hub of what that. work is across the multiple versions but.

that almost seems like a fun. project of a couple of engineers within. within google as opposed to a serious. effort to make the world's science. accessible but but going back to just. the. the journals when you're talking about. that lex i i believe that. in that front i think we might be past. the event horizon so i think the. the the model the business model for the. journals you know doesn't make sense. they are a middle layer that is not. adding a lot of value and you see a lot.

of motions whereas like in europe a lot. of the the. papers that are get. are funded by the european union they. will have to be um uh. open to the public and i think there's a. lot of bill gates to like the the what. the gates foundation funds like they. they demand that it then it that it's uh. accessible to everybody oh interesting. so i think it's it's the question of. time before that that wall kind of falls. and and that is going to open a lot of. possibilities um because you know.

imagine if if you had like the layer of. like that gigantic layer of papers all. available online. um you know that unlocks a lot of. potential as a platform for people to. build things on top of that but i think. it's what you're saying it is weird like. you can literally. go and listen to any song that was ever. made. on your phone right you open spotify and. you might not even pay for it you might. be on the free version and you can. listen to any song that has ever made. pretty much.

but. there's like you you don't have access. to a huge percentage of academic papers. which is just like this fundamental. knowledge that we're all funding but you. as an individual don't have access to it. and and somehow you know like the. problem for music got solved. uh but for papers it's still like it's. just not yet it could be ad supported. all those kinds of things and that. hopefully that would change the way we. do science that's the most exciting. thing for me. is uh especially once i started like.

making videos in this. silly podcast thing i started to realize. like. that if you want to do science one of. the most effective ways is to do uh like. couple. the paper with a set of youtube videos. like explaining it like. yeah that also seems like there's a lot. of room for disruption there what is the. paper 2.0 gonna look like i think like. latex and the pdf. seems like if you. it's interesting if you look at the.

first paper that got published in nature. and if you look at the paper that got. published in nature today look at the. two side by side they are fundamentally. the same. and. even though like the paper that gets. published today you know. you get even even code like right now. people put like code like on on a pdf. like and. there are so many things that are. related to papers today you know you use. you have data you have code um you might. need videos to to better explain the.

concepts so it's it i i think for me. it's natural that there's going to be. also an evolution there that papers are. not going to be just the static pdfs or. latex. there's going to be a next uh next. interface so in academia a lot of things. that are judged your judge by is often. quantity not quality. i i wonder if there's a opportunity to. have like. i tend to judge people by the best work. they've ever done as opposed to. i wonder if there's a possibility for.

that to encourage sort of um focusing on. the quality. and not necessarily in paper form but. maybe a subset of a paper subset of idea. almost even a blog post or an experiment. like why does it have to be published in. a journal. yeah to be. legitimate. and and it's just interesting that he. mentioned that i also think like yeah. it's why why why is that the only format. why can't a blog post or. uh we were even experimenting. experimenting with these a few months.

ago or can you actually like publish. something. or. um. like a new scientific breakthrough or um. or something that you've discovered in. the form of like a set of tweets. yeah the twitter thread why can't that. be possible. and um. we were expanding experimenting with. that idea uh we even um yeah we ran a. couple of of like some people submitted. a couple of those like i think the limit. was three or four tweets yeah uh maybe.

it's a new way to look at a you know a. proof or something but uh i think it. just serves to show that there should be. other ways to publish like scientific. discoveries that don't fit the paper. format well. but so even with the twitter. thread. it would be. it would be nice to have some mechanism. of formalizing it and making it stat. making it into an nft. like. a concrete thing that you can reference. is a link that's unique. because uh i mean everything we've been.

saying. all of that. while being true. it's also true that. the. constraints and the formalism of a paper. works well it like forces you. constraints forces you to narrow down. your thing and. and uh literally put it on paper. but you know. i agree uh make concrete and that's why. i mean it's not broken it's just could.

be better and that's the main idea i. think there's something about writing. whether it's a blog post or twitter. thread or a paper. that's really nice to to concretize a. particular little. idea that they can then be referenced by. other ideas then it can be built on top. of with other ideas. so uh let me ask you've read quite a few. papers.

you've uh annotated quite a few papers. let's talk about the process itself how. do you advise people read papers. or maybe you want to broaden it beyond. just papers but just. read. concrete pieces of information to. understand the insights that lay within. i would say for paper specifically i. would i would bring back kind of what. louise was talking about it is that it's. important to keep in mind that papers. are not optimized for ease of. understanding and so right there's all.

sorts of restrictions in size. and format and and language that they. can use and so it's important to keep. that in mind and so that if you're. struggling to read a paper doesn't. that might not mean that the underlying. material is actually that hard. and so. so that's definitely something that that. especially for us that we we read papers. and most of the times the lead papers. are completely outside of our. of our comfort zone i guess and and to.

be completely new areas to us um. so i always try to to keep that in mind. so there's usually a certain kind of. structure like abstract introductions. methodology. uh depending on the community and so on. is there something about. the process of like how to read it. whether you want to skim it to try to. find the parts that are easy to. understand or not. uh reading it multiple times. is there any kind of hacks that you can. comment on i remember like feynman had.

this this kind of hack when it was. reading papers where. he would basically. um. would i think i believe he would read. the conclusion of the paper. and we would try to just um see if he. would be able to figure out how to get. to the conclusion in like a couple of. minutes by himself. and um and he would read a lot of papers. that way and i think fermi also did that. almost and fermi was known for doing a. lot of back of the envelope calculation.

so he was a master at doing that um. in terms of like especially when. when reading a paper i think a lot of. times people might. feel discouraged about the first time. you read it. you know it's very hard to grasp or you. don't understand a huge fraction of the. paper. and i think it's having read a lot of. papers in my life i think i've in peace. with like the fact that you might spend. hours where you're just reading a paper. and jumping from paper to paper reading.

citations. and um like your level of understanding. of sometimes of the paper is very close. to zero percent and all of a sudden you. know everything kind of. makes sense and and in your mind and. then you know you have this quantum jump. where all of a sudden you you you. understanding the big picture of the. paper and uh i i. and and this is an exercise that i have. to when reading papers and especially. like more complex papers like okay you.

don't understand because you're just. going through the process and just keep. going and like and it. might feel super chaotic especially if. you are jumping from reference to. reference you know you might end up with. like 20 tabs open and you're reading a. ton of other papers but it's just. trusting that process. that at the end like you'll find light. and i think for me that's a good. framework. when reading a paper it's hard. because you know you might end up. spending a lot of time and you it looks. like you're lost. but uh but.

that's the process to actually um you. know understand what they're talking. about in the paper. yeah i think that process. i enjoy i've found a lot of value in the. process especially for things outside my. field. of reading a lot of related work. sections and kind of go going down that. path of getting a big context of the. field because. what's especially when they're well. written. there's opinions injected into the. related work like what work is important. what is not and if you read multiple.

related work sections that cite or don't. cite each other like the papers. you get a sense of where the field where. the tensions of the field are. where this where the field is striving. and that helps you put into context like. whether the work is radical whether it's. overselling it itself whether it's. underselling itself all those things. uh and on adding on top of that. i find that often the related work. section. is the most.

kind of accessible and readable part of. a paper because it's kind of uh it's. brief to the point it's trying like. summarizing it's almost like a wikipedia. style article. the introduction is supposed to be a. compelling story or whatever but it's. often like overselling there's like an. agenda in the introduction. the related work usually has the least. amount of agenda except for the few. like elements where you're trying to uh. talk shit about previous work where. you're trying to sell that you're doing.

much better but other than that when. you're just painting where the where the. field. came from or where the field stands. that's really valuable and also again. just to agree with finding the. conclusion it's like i get a lot of. value from the. breadth first search kind of read the. conclusion. then read the related work and then. go through the references in the related. work read the conclusion read the. related work and just go down the tree. until you like hit dead ends or run out.

of coffee and then through that process. you go back up the tree and now you can. see the results in their proper. in their proper context unless of course. the paper is truly revolutionary which. even that process will help you. understand that is in fact truly. revolutionary. you've also um. you talked about just following your. twitter thread in a. depth first search you talked about that. you read uh. the book on. grisha pearlman go to brahman.

and then you would you had a really nice. twitter thread on it and. you were taking notes throughout so. at a high level is there suggestions you. can give on how to take good notes. whether it's we're talking about. annotations or just for yourself to try. to. put on paper ideas as you progress. through the work in order to then like. understand the work better for me i. always try not to underestimate how much. you can forget uh within six months.

right after you've read something i. thought you're gonna say five minutes. but yeah six months is good yeah or. or even shorter and so. that's something i always try to keep in. mind and uh and it's and it's often i. mean. every once in a while i'll read back a. paper that i annotated on vermont and. it's and uh and i'll read through my own. annotations and it's uh and i've. completely forgotten what i had written. and but it also. it also it's interesting because in a. way after you just understood something.

you're kind of the best possible teacher. that can teach your future self. uh yeah you know after you've forgotten. it uh. you can you're kind of your own best. possible teacher at that moment and so. it's it can be great to try to capture. that. it's it's brilliant it just made me kind. of. realize. it's really nice to to put yourself in. the position of teaching an older. version of yourself exactly that returns.

to this paper almost like thinking it. literally. that's underexplored. but it's it's super powerful because you. were the person that you can like if you. if you look at the scale from like one. not knowing anything about the topic and. ten. like you are the one that progressed. from one to ten and you know which steps. you struggled with so you're the really. the best person to help yourself make. that transition from one to ten. and um a lot of the times like. and we don't i really believe that the. framework there we have to like just.

expose ourselves to like be talking to. like us when we were an expert when we. were taking that class and we knew. everything about quantum mechanics and. then six months later you don't remember. half of the things how could we make it. easier for a like to. have those conversations between you and. your past self past expert self. um. i i think there there might be you know. it's an underexplored idea i think notes. on paper are probably not the best way. i'm not sure if it's a combination of. like video.

audio where it's like you have a guided. framework that you follow to extract. information from yourself so that you. can later kind of revisit. to make it easier to to remember but. that's i think it's an interesting idea. worth worth exploring that not i've i. haven't seen a lot of people kind of. trying to. uh distill that problem. you know i'm creating the kind of tools. i find if i record it it sounds weird. but i'll take notes but if i record.

audio. like um like little clips of thoughts. like rants. that's really effective at capturing. something that notes can't. because when i replay them for some. reason. it loads my brain back into where i was. when i was reading that in a way that. notes don't like when i read notes i'll. often be like what what. what was i what was i thinking there but. when i listened to the audio yeah it.

brings you right back to that place so. there might and. maybe with video with visual that might. be even more powerful i think so yeah. and and i think just the process of. you know verbalizing it. that alone kind of makes you have to. structure your thought and and put it in. a way that somebody else could come and. understand it and and just the process. of that is useful to to organize your. thoughts and and. and um yeah just just that alone does. the firmware's library journal club have.

a like a video component or no. we no not natively we sometimes will. include uh videos but it's always. embedded do people like build videos on. top of it to explain the paper because. you're doing all the hard work of. understanding deeply the paper. not we haven't seen that happening too. much but uh we were we were actually. playing around with the idea of creating. some sort of podcast version where we. try to distill the paper. on an audio format that not maybe you. could have access.

might be trickier but you there's. definitely people that could be. interested in the paper in that topic. but are not willing to read it but they. might listen to a 30 minute episode on. that paper yes you could reach more. people and and you might even bring the. authors to the conversation but it's. tricky especially for like more. technical papers we've we've thought. about that doing that but we haven't uh. like converge so if you have any. uh well i'm gonna take that as a a small. project to take one of you one of the. females almost like.

half advertisement and half as a. challenge for myself to take take one of. the annotated papers and like use it as. a basis for creating a. quick video. i i i've seen like um. hopefully i'm saying the name correctly. but. machine learning street talk. i think that's the name of the show the. that i recommend highly that's the right. thing. but uh they they do exactly that which. is multiple hour breakdown of a paper. with video component. sometimes with authors.

um people love it it's very effective. there's there's also i've seen i haven't. seen the entire in its entirety but i've. seen like the the founder of comma dot. ai george yeah i've seen him like just. taking a paper and then. you know distilling the paper and coding. it coding it sometimes during 10 hours. yeah and um he was able to you know get. a lot of people interested in in that. and viewing him so i'm a huge fan of. that. like uh.

george is a personality i think a lot of. people like listen to this podcast for. the same reason it's not necessarily the. contents it's they they they like to. listen to like a. a silly. russian who has a childlike brain and. mumbles and all those like struggle with. ideas right and george is a madman who. people just enjoy like how is he going. to struggle in implementing this. particular paper how is he going to. struggle with this idea it's fun to. watch and that actually pulls you in the. personality is important there true but.

there's lots there's you know i agree. with you but they're also it's visible. like it's. there's an extraordinary ability that is. there like is talented and you need to. have. there's a craft and this guy definitely. has talent and he's doing something that. is not easy and i think that also draws. the attention of people oh yeah and and. like the other day we were actually we. ran into this youtube channel of this. guy that was restoring art. right um yeah and. and um it was basically just a video of.

him like his the production is really uh. like really well done and it's just him. taking really old um pieces of of art. like and then paintings and then. restoring them but he's really good at. that and he describes that process and. that draws attention uh draws the. attention of people regardless of your. craft be it like annotating your paper. or like responsibilities. excellence yeah like george is. incredibly good at programming. like quick like you know those uh.

competitive programmers like top motor. and all this kind of stuff he has the. same kind of element where the brain. just jumps around really quickly and. that's uh yeah. just. like yeah it's motivating but but. and you're right in in watching people. who are good at what they do it's. motivating even if the thing you're. trying to do is not what they're doing. it's just like contagious when they're. really good at it and the same kind of. analysis with the paper i think. so not just like the final result but.

the process yeah struggling with it. that's really interesting yeah i think i. mean i think twitch proved that like. you know that there's really a market. for for that for watching people. do things that they're really good at. and. and you'll just watch it you will enjoy. that that that might even uh spike your. interest in that specific topic and. yeah and people people will enjoy. watching sometimes hours on end of. yeah great craftsmen. do you mind if we talk about some of the. papers do any papers come to mind.

that have been annotated on the. vermont's library. the papers that we annotated can be. about completely random topics but. that's part of what we enjoy as well it. forces you to explore these topics that. otherwise maybe you'd never run into. uh and so. so the ones that come to mind that to me. are fairly random but one that i i. really enjoyed. learning more about is um a paper. uh written by a mathematician actually. tom apostol and uh about a.

a tunnel. in uh greek island off the coast of. turkey. i think it's already random. so this uh okay so what's interesting. about this tunnel so this tunnel um was. built in the sixth century bc. and um. and it was built in this. in the island of samos uh which is as i. said off the coast of turkey and um. right they had the city on one side and.

the other mountain and then they had. a bunch of springs on the other side and. they they wanted to bring water into the. city. um did building an aqueduct would be. pretty hard because of the way the. mountain was shaped and it would also. you know if they if they were under a. siege like. they could just um easily destroy that. aqueduct and then the water wouldn't. have any water supply the the city. wouldn't have any water supply and so. they decided to build a tunnel. and they decided to try to do it quickly.

um and so. the. they started digging. uh from both ends at the same time. through the mountain right and so. like when you start thinking about this. it's it's a fairly difficult problem and. this is like 6th century bc so. you had very limited access. to you know the mathematical tools that. you had at the time were very limited. and so what this paper is about is about. the story of how they built it and about. the fact that for about 2000 years kind.

of the accepted the accepted explanation. of how they built it was actually wrong. and so this tunnel has been famous for a. while there are a number of historians. that talked about it since ancient egypt. and um and the method that they. described uh for for building it um is. is. uh was just wrong and and so these these. researchers went there and and were able. to figure figure that out and so. basically kind of the way that they.

thought they had built it was basically. if you can imagine looking at the. mountain from the top and you have the. mountain and then you have both. entrances um. and so what they what they thought and. what this is what the ancient historians. described is that they. effectively tried to draw a right angle. a right angle triangle um. with the two entrances at each end of. the hypotenuse and the way they did is. like they would go around the mountain. and kind of walk in a grid fashion and.

then you can you can figure out uh the. two sides. of the triangle and then after you have. that triangle you can. effectively draw two smaller triangles. at each entrance that are. proportional to that big triangle. and then you kind of have arrows. pointing in each way. and then you can you know at least that. these that you have a line going through. the the mountain that connects both. entrances. the issue with that is like once you.

once you go to this mountain and you. start thinking of doing this you realize. that especially given that the tools. that they had at the time that your. error margin would be too small. you wouldn't be able to do it uh you you. you. the just the fact of of trying to to. build this triangle in that fashion the. error would accumulate and you would end. up missing you'd start building these. tunnels and they would miss each other. so the task ultimately is to figure out. like really perfectly as cl as close as. possible the direction you should be.

digging first of all that it's possible. to have a straight line through and then. what that the direction would be and. then you're trying to infer that by. constructing a right triangle. by doing i i'm not exactly sure about. how to do that rigorously like by. tracing the mountain by walking along. the mountain how to you said grids yeah. you kind of walk as if you were in a in. a grid and so you just walk in right. angles i so right but then you have to. walk really precisely then exactly you.

have to use tools to measure this and. then the terrain is probably yeah very. messed up so this makes more sense in 2d. and 3d gets even weirder. so okay gotcha but so this method was. described by like an ancient egyptian. historian i think hero of alexandria and. um and then for about like yeah for. about 2000 years that's that's how like. that's how we thought that they had. built this this tunnel um. and then in the end then these. researchers went there and and found out.

that actually they they must have had to. to use other methods and and then in. this paper they describe these these. other methods and of course they can't. know for sure but there's uh they. presented a bunch of plausible. alternatives the one that for me was is. the most plausible is that what they. probably must have done is to use. something that is similar to. an iron sight on a rifle the way you can. line up uh your rifle with the target. off in the distance by by having an iron.

sight. um. and uh and they they they must have done. something similar to that effectively. with tree with three sticks and that way. they were able to. line up. sticks. along the side of the mountain that were. all on the same height. and so that then you could get to the. other side and you could cut and then. you could draw that line. so this for me is the most plausible. way that they might have done that and.

they. but then they they they describe this in. detail and other possible approaches in. this paper so this is a mathematician. doing this yeah this is a mathematician. that did this um which i suppose is the. right. mindset instead of skills required to. solve an ancient problem right yeah. yeah there's mathematicians and. engineers a lot of things because they. didn't have uh computers or drones or. lidar back then or whatever technology. you would use modern day for civil. engineering yeah and another fascinating.

thing is that like. you know after. effectively after the the downfall of. the roman civilization people didn't. build tunnels for about a thousand years. we go a thousand years without tunnels. and then like only in like in late. middle ages that we start doing them. again but uh but here is the tunnel like. 6th century bc like incredibly limited. mathematics and they and they build it. in this way um. and and and for and it was a mystery for. for a long time exactly how they did it.

and then these mathematicians went there. and and uh. and and basically with no archaeology. kind of background we're able to figure. it out how do annotations for this paper. look like what is it uh what's a. successful annotation for paper like. this. yes so sometimes you're uh for this. paper um. sometimes adding some more context uh on. on a specific um. part like sometimes they they mentioned. for instance um. these. instruments that were common in ancient.

greece and an ancient rome. for for building things and uh and and. so in some of those annotations i. described these instruments in more. detail and how they worked because. sometimes it can be hard to to visualize. these um. then this paper um i forget exactly when. when this was published uh i believe. maybe maybe the 70s um but then there. was further research into this tunnel. and more interesting other interesting.

aspects about it i add those to that. paper as well there's historical context. that i also go into uh there. for instance the fact that as a as i. said that effectively after the downfall. of the roman empire no tunnels were. built like that's something that i that. i go that i that i added to the paper as. well. yeah so so this is so when other people. look at the paper. how did they usually consume the. annotations so they it's like is there a. commenting feature is uh. i mean like. this is a really enriching experience.

the way you read a paper. what what aspects do you do people. usually talk about that they value from. this. so yeah so anybody can just go on there. and and either add a new annotation or. other a comment to an existing. annotation and so you can start a kind. of a thread uh within an existing. annotation um and that's something that. happens relative frequency and then. because i was the original author of the. initial annotation i get pinged and so.

often times i'll go back and and. and add on to to that thread how did you. pick the paper that's i mean first of. all this whole process is really. exciting i'm gonna especially after this. conversation i'm gonna. make sure i participate much more. actively. on papers that i know a lot about and on. paper i know nothing about i shouldn't. bother when i say the paper. i would love to i also i mean i i. realized that uh there's a like it's an. opportunity for people like me.

to publicly annotate a paper. like. like or do an ama around the paper like. yeah exactly. but yeah but like be um. be in the conversation about a paper. it's like a place to have a conversation. about an idea you could the other way to. do it that's much more ad hoc is on. twitter right but this is more like. formal and you could actually probably. integrate the two they have a. conversation about the conversation so. the twitter is the conversation about a. conversation and the main conversation.

is in the space of annotations there's. an interesting effect that we we see. sometimes with the annotations on our. papers is that a lot of people. especially if we the annotations are. really well done people sometimes. are afraid of adding more annotations. because they see that as a kind of a. finished work yes and so they they don't. want to pollute that or. and especially if it's like a silly. question this is. i don't think that's good i think you. know. we should as much as possible try to.

lower the barrier for someone to jump in. and ask questions i think it only like. most of the times it adds value but it's. some feedback that we got from users and. and readers. um. i'm not exactly sure how to. to kind of fight that but um well i. think i. i think if i serve as an inspiration. in any way. is by asking a lot of dumb questions and. saying a bunch of dumb shit all the time. and hopefully that inspires the rest of.

uh other folks to do the same because. that's the only way to knowledge i think. is to. be willing to ask the dumb questions and. and there are papers that are like um. and we have a lot of papers on formats. where it's just one page or really short. papers. and you we have like the shortest paper. ever published in a math journal like. with like just a couple of words. one of my favorite papers on the. platform is actually a paper um written. by enrico fermi yeah and the title of. the paper is myop's i think it's my. observations at trinity so basically.

fermi was part of the manhattan project. so he was in new mexico when um they. exploded the first atomic bomb. and so he was a couple of miles away. from the explosion and he was probably. one of the first persons to calculate. the energy of the explosion and so the. way he did that was he took a piece of. paper and he tore down a piece of paper. in little pieces and when the bomb. exploded. the trinity bomb was the name of the.

bomb like he waited for the blast to. arrive at. where he was. and then he threw those pieces of paper. in the air and he calculated the energy. based on the displacement of the paper. the pieces of paper and then he wrote a. report which was classified until like a. couple of years ago one page report like. calculating the energy of the explosion. uh it's so badass and i i we actually. went there and kind of unpacked and like. yeah i think it just mentions basically. the energy and we we actually went and. one of the annotations is like.

explaining how he did that. um i wonder how accurate he was. it was maybe i think like 20 20 or 25. off uh then there was another person. that actually calculated the energy. based on uh images after the explosion. at the rate uh and the rate that which. the the the like the mushroom of the. explosion expanded and it's more. accurate to calculate the energy based. on that um and i think it was like 20 20. off but it's it's really interesting. because you know fermi was known for all.

these being a master at this back of the. envelope calculations always like the. the fermi problems are well known for. for that um and it's super interesting. to see like that just one page report. and was also actually classified and. it's interesting because a couple months. ago when the beirut explosion happened. there was a video circulating of these a. bride that was doing a photo shoot. when the explosion in beirut happened. and so you can see a video of her with. the wedding dress and then the explosion. happens and the blast arrives at where.

she was she was a couple of miles away. from the glass and you can see like um. the displacement of the dress as well. and i actually looked and that video. went viral on twitter and i actually. looked at that video and based i used. the same techniques that fermi used to. calculate the energy of the explosion uh. based on the displacement of the dress. and you could actually see where where. she was at the the distance from the. explosion because there was a store. behind her and you could look the name. of the store and and so i calculated.

that it was the distance and then you. can then based on the distance where she. was from the the explosion and also on. the the displacement of the dress like. because you can when the blast happens. like you can see the dress going back. and then. going back to the original position and. like by just looking at like how much. the the dress moved you can. estimate the explo the energy of the. explosion i assume you published this. on twitter it was just a a twitter. thread uh but it it actually like a lot. of people share that and it was picked.

up by a couple of of um news outlets but. i i was hoping it would be like a formal. title and it would be an archive no no. no no maybe you submitted it just the. twitter the twitter thread but it was. interesting because it was exactly the. same method that fermi used. is there something else that jumps to. mind like what is there something. i know like in terms of papers like i. know the bitcoin paper is super popular. is there something interesting to be. said about any of the white papers in. the cryptocurrency space. yeah the.

the bitcoin paper was the first paper. that we put on for mods and uh why why. that why that choice as the first paper. this was a while ago and it was one of. the papers that i read and then. and then kind of explained it to to. louisiana or to other friends that do. this journal club with us. and um. i did some research in cryptography uh. as an undergrad and so it was a topic. that i was interested in um but even for. me that i i had.

that background but. reading the bitcoin paper. it took me a few weeks to really kind of. wrap my head around it it's it's right. it's it uses very spartan precise. language in a way it's like you feel. like you can't take any word out of it. without something falling apart. and uh and it's all there i think it's a. beautiful paper and it's it's it's. very well written of course but. um. you know we wanted to try to make it. accessible so that anybody that maybe is.

an undergrad in computer science could. go on there and then and and know that. you have all the information. in in that page that you're going to. need to understand the mechanics of. bitcoin and so like i explain you know. the basic uh. public key cryptography that you need to. to know in order to understand it you. can explain okay what are the properties. of a hash function and how they are. useful in this context um explain what a. merkle tree is so a bunch of those basic.

concepts that maybe if you're reading it. for a first time and you're an undergrad. and you know you don't know those terms. you're going to be you know discouraged. because maybe okay now i have to go and. google around until i understand these. before i can make progress in the paper. um. and and this way it's all there you know. so so there's a. magic to. also to the fact that over time more. people went on there and and added. further annotations so the idea that the. paper gets easier and more accessible. over time but that's still you're still.

looking at the original content the way. the. the author. intended it to be uh but there's just. more context and the toughest bits have. have. more in-depth explanations. okay i think like there's a there's so. many interesting papers uh there like. i remember reading the paper that was. written by freeman dyson on the. like the the first time that he. explained or he came up with the concept. of the dyson sphere and he he put that.

out like it's again it's one page paper. um and he what he explained was that. eventually if a civilization develops. and and grows there's going to be a. point where when the resources on the. planet are not are not enough for the. energy requirements of that civilization. so if you want to go. the next step is you need to go to the. next star and extract energy from that. star. and the way to do it is you need to. build some sort of cap around the star. that extracts the energy so he theorized.

this idea of the the dyson sphere and he. went on to kind of analyze how he would. build that the stability of that sphere. like if something happens if there's. like a small oscillation with that fear. collapsing to the star or no what what. would happen and even went on to uh kind. of say that a good way for us to look. for signs of intelligent life out there. is to look for signals of these dyson. spheres. and because you know according to the.

law of second law of thermodynamics like. this there's going to be some a lot of. infrared radiation that is going to be. emitted as a consequence of extracting. energy from the star and we should be. able to see those signals of like. infrared if we look at the sky but all. these like from the introduction of the. concept like the pro how to build the. dyson sphere the problems of like having. a dyson sphere how to detect how that. could be used as a signal for. intelligence like really that's all in. the paper all in one like one page paper. and it's like it's it's for me it's.

beautiful it's like where was this. published i don't remember it. it's fascinating that papers like that. could be. yeah i mean the guts it takes. to put that all together in a paper you. know that that kind of challenges our. previous discussion that of paper i mean. papers can be beautiful you can play. with the format right it. but there's a lot to unpack there that's. like the the that's the the starting. point but it's it's it's beautiful that. you're able to put that in one page. and then people can build on top of that.

and but the key ideas are there yeah. exactly. what about have you looked at any of the. the big seminal papers throughout the. history of science like you look at. simple like einstein papers. have any of those been annotated yeah. yeah no we we have some more seminal. papers that. that people will have heard about um you. know we have the. the dna double helix paper on there. we have the higgs boson. paper.

um yeah there's papers that that we know. that it's. they're not going to be finding out. about them because of us but it's papers. that we think. should be more widely read and that. folks would benefit from having some. annotations there and so we also have a. number of those a lot of like discovery. papers for fundamental like particles. and all that there's we have a lot of. those on from us library. um yeah we i would like to end we. haven't annotated that one but i'd like.

to on the riemann hypotheses that's a. really interesting paper as well um and. and but we haven't annotated that one. but there's a lot of like more. historical landmark papers. um on the platform have you done uh. point correct conjecture with uh with. perlman that's too much that's too much. that's too much too much for me but it's. uh. it's it's interesting that you know and. going back to our discussion like the. the poincare paper was like published on. archive and and it was not on a journal. like the three papers and yeah what do.

you make of that i mean he's such a. fascinating human being exactly i. mentioned to you offline that i'm going. to russia he's somebody i'm. really trying to interview yeah well. so. i definitely will interview him i um and. i believe i will i believe i can i just. don't know how to. i know where you live so. here okay my my uh. my hope is my conjecture is that if i. just show up to the house and look. desperate enough.

uh that uh or threatening now for some. combination of both. that like the only way to get rid of me. is to just get the thing done that's the. hope it's actually interesting that you. mentioned that because i after i um so a. couple of weeks ago i was searching for. like stuff about paramount paramount. online and ended up on this twitter. account of like this guy that claims to. be paramount perlman's assistant. and he is like he has been posting a. bunch of pictures like next to paramount. you can see like permanent in in a. library and he's like next to him like.

taking a selfie or like firm and walking. on the street and like maybe you could. reach out to. this assistant then i'll send you i'll. send you this twitter account so. maybe you're on to something no but but. going back to like pheromone is super. interesting because the fact that he. published the the. the proofs on archive is what was also. like a way for him to because he really. didn't like the scientific publishing. industry and the fact that you had to. pay. to get.

access to to articles and that was a. form of like protest and that's why he. published um those papers there i mean i. i think paramount is just a fascinating. like character and for me it's this kind. of ideal of a platonic ideal of what a. mathematician should be you know it's. it's someone that is you know it just. cares about deeply cares about. mathematics you know it cares about fair. attribution of um. disregards money and um. and and like the fact that he published.

like on archive was is a good example of. what about the fields metal that he. turned down the fields metal what's. what's yeah. what do you make of that yeah i mean. if you look at like the reasons why he. rejected the fields medal so after so. paramount did a post talk in the us and. when he he came back to russia. um. do you know how good his english is i. think it's very fairly good it's pretty. good i think it's really good especially. given lectures in american union but i. haven't been able to listen to anything. well certainly not listen but i haven't.

been able to get anybody because i know. a lot of people have been to those. lectures. i'm not able to get a sense of like. yeah but how strong is the accent what. are we talking about here is this gonna. have to be in russian is it gonna have. to be in english it's fascinating but he. writes the papers in english so it's. true like there's there's but there's so. many like such a fascinating character. and um there are a couple of examples. like him like at i think 28 or 29 he. proved like a really famous uh. conjecture called the sulk conjecture i. believe it was like in a very short.

four-page proof of that it was a really. big breakthrough then he went to. princeton to give a lecture on that and. after the lecture. the the chair of the math department at. princeton a guy called peter sarnock. went up to the parliament was trying to. recruit him. trying to offer him a position at. princeton and he was and at some point. he asked for perlman's resume and. fellman responded saying just gave a. lecture on like this really tough. problem why do you need my resume like.

i'm not gonna send you like i just. proved like my value. but uh but going back to the fields. metal like when when perlman went to. back to russia he. he arrived at a time where the. the salary of post docs was so much off. in regards to inflation that they were. not making any money like they. people didn't even bother to pick up the. checks at the end of the month because. it was like ridiculous but thankfully he. had some money that he had uh gained.

while he was doing his post talk so he. just concentrated on like. the poincar the the prank reconjecture. problem which he when he when he took. that um it took it after it was reframed. by this mathematician called richard. hamilton which posed the problem in a. way that it turned into this super like. math olympiad problem with like perfect. boundaries well defined and that was. perfect for paramount to attack and so. he spent like seven years working on. that and then in 2002 he started.

publishing those papers on archive. and. people started jumping on that reading. those papers and there was like a lot of. excitement around that a couple of years. later there were two researchers i. believe was they were from harvard that. but. took paramount pearlman's work they. sanded some of the edges and they. republished that. saying that you know. based on pearlman's work they were able. to figure out the the pronghorn. conjecture. and then there was um at the time at the.

in the international um. conference of of mathematics in 2000. 2006 i believe that's when they were. going to give out the fields medal there. was a lot of debate of like oh. who's who's like we should get the. credit for. solving this big problem and for. apparelmen it like it. it felt really sad that people were even. considering that he was not the person. that solved that. and and the claims that.

those like researchers uh when they. published after paramount there were. false claims that they were the ones. they just sanded a couple of edges like. parliament did all the really hard work. and so. just just the fact that they doubted. that pearman had done that like was. enough for him to say i'm not i'm not. interested in this prize and that was. one of the reasons why he rejected the. fields medal it then you also rejected. the clay prize so the poincare. conjecture was one of the millennium. prices there was a million dollar prize. associated with that problem and that.

has to have to do with the fact that for. them to attribute that price i think it. had to be published on a journal yes the. proof and again. paramount principles of. like interfered here and and he also. just didn't care about the money he's. like um clay i think was a businessman. and he's like doesn't have to do. anything with with mathematics i don't. care about these like um. that's one of the reasons why we. rejected that yeah there's. it's hard to convert into words but.

at mit i'm. distinctly aware of the distinction. between when i enter a room there's a. certain kind of music. to the way people talk when we're. talking about ideas. versus. what that music sounds like when we're. talking. when it's like bickering. in the space of like whether it's. politics or funding. or egos. it's a different sound to it.

and i'm. distinctly aware of the two. and i kind of sort of to me personally. happiness what was just like swimming. around. the one that like is the political stuff. or the money stuff and all that. uh or egos. uh. and i think that's probably what. prominent is as well like the moment he. senses there's any as with a feels. matter like the moment you start. to have any kind of drama around credit. assignment all those kinds of things.

it's almost not that it's important who. gets the credit it's like the drama in. itself gets in the way of the. exploration of the ideas or the. fundamental thing that makes science. so damn beautiful and and you can really. see that there's also a product of that. russian school of like doing science. and you can see that that um. that people were you know during the. cold war a lot of mathematicians they. were not making any money they were. doing math for the sake of math. like for the intellectual.

pleasure of like solving a difficult. problem yeah and you know even even if. it was a flawed system and there were a. lot of problems with with that. there's these they were able to to. actually achieve these and uh there were. a lot of imperiment for me is the. perfect product of that it just cared. about like working on tough problems he. didn't care about anything else it was. just math. you know pure math yeah there's a like. for the broader audience i think another. example of that is. like professional sports versus olympics.

i've especially in russia i've seen that. clear distinction. where because the state manages. so much of the olympic process in russia. as people know the steroids yes yes yes. but outside of the steroids thing uh is. like the athlete can focus on. the pure. artistry of the sport like. like not worry about the money not just. in the way they talk about it the way.

they think about it the way. they define excellence versus like. in the. perhaps a bit of a capitalist system in. united states with. american football with baseball. basketball. so much of the discussion. is about money. now of course at the end of the day it's. about excellence and artistry and all. that but. when the culture is so richly grounded. in discussions of money and. uh sort of this capitalistic like uh.

merch and businesses and all those kinds. of things it changes the nature of the. activity. and it's in a way that's hard again to. describe in words but when it's purely. about the activity itself. it's almost like. you quiet down all the noise enough to. hear the signal enough to hear the. beauty like whenever you're talking. about the money that's when. the marketing people come and the. business people the non-creators come.

and they fill the room and there's they. create drama and they know how to create. the drama and the noise as opposed to. people who are truly excellent at what. they do the. the person in their arena right. like when you remove all the money and. you just let. that thing shine that's when true. excellence can and can come out and that. was. of the few things that work with the. communist system the soviet union to me. at least as somebody who loves sport and. loves mathematics and uh science.

that worked well removing the money from. the picture. uh. you know not that i'm um. not that i'm saying poverty is good for. science. there's some level in which not worrying. about money. is good for science it's a weird i'm not. exactly sure what to make of that. because capitalism works really damn. well yeah but. it's um. it's tricky how to find that balance one.

fields metal list that is interesting to. look at and i think you mentioned it. earlier but is cedric villani which is. might be the only. uh. phil's medalist that is also a. politician now but so it's this it's. this brilliant french mathematician. that won the fields medal and and after. that he decided that. one of the ways that he could have. could have. you know the biggest leverage kind of is. in pushing science in the direction that. he thinks.

science should go would be to to try to. go into politics and so that's what he. did and and uh. and the israel i'm not sure if he has. won. in any election but i think he's running. for a mayor. of paris or something like that but it's. this brilliant mathematician that. before. winning the fields medal had only been. just a brilliant mathematician but but. after that he decided to go into. politics to to try to to have an impact. and try to change some of the things. that he he would complain about before.

so so there's that component. as well. yeah and i've always thought mathematics. and science should be like like james. bond. would in my eyes i think be sexier if. you did math like we should as a society. put. excellence in mathematics. at the same level as being able to kill. a man with your bare hands like those. are both useful feature like. that's admirable it's like oh like that. makes you like that makes the person.

interesting. like being extremely well read about. history or philosophy being good in. mathematics being able to kill a man. with bare hands those are all the same. in my book so i think all are useful for. action stars. and i think the society will benefit for. uh for giving more value to that like. one of the things that bothers me about. american culture. is the. i don't know the right words to use but. like the nerdiness associated with. science. like.

like in i i don't think nerd is a good. word in in american culture because uh. it's seen as like weakness there's like. images that come with that and it's fine. you could you could be all kinds of uh. shapes and colors and personalities but. like. to me. uh having sophisticated knowledge in. science being good at math doesn't mean. you're weak. in fact it could be the very opposite.

and so it's it's an interesting thing. because it was very much differently. viewed in the uh in the soviet union so. i know for sure. as an existence proof. that it doesn't have to be that way but. it um. i also feel like we lack a lot of. like role models in terms if you ask. people like. mention. to mention one mathematician that they. know that is alive today i think a lot. of people would struggle. to answer that question um. and i also think.

i love neil degrasse tyson okay. but. there is uh. having more role models is good like. different kinds of personalities he he. has kind of fun and and it's very it's. uh like. bill nye the science guy i don't know if. you guys know him so like that spectrum. that yeah but there there's not. like feynman is no longer there. uh those kinds of personalities. even carl sagan yeah.

like a seriousness that's like not. playful like not apologetical yeah. exactly not apologetic about being. knowledgeable like. like. in fact like the kind of energy. where. you feel. uh self-conscious about not having. thought about some of these questions. right just like when i see james bond i. feel bad about that i don't. have never killed a man like i need to.

make sure i fix that right that's the. way i feel so the same way i want to. feel like that way well carl sagan talks. i i feel like i need to have that same. kind of seriousness about science like. if i don't know something i want to i. want to know well. what about terence tao. he's kind of a superstar what are your. thoughts about him true he's probably. one of the most famous mathematicians. alive today and problem of i mean. regardless of like is of course uh. he want to feel the fields medal is. really smart and talented mathematician.

um. it's also like a big inspiration for us. at least. for some of the work that we do with. formats library so terence style is is. known for having you know a big blog and. he's pretty open about. like his research and he also. he tries to make his work as public as. possible um. through his blog posts um in fact. there's a really interesting um. problem that got solved a couple of.

years ago so tao was working with um on. a problem on an erdos problem actually. so if paul erdogan was this. mathematician from hungary and it was. known for like um. the airdosh. for a lot of things but one of the. things that he was also known was for. the erdos problem so he was always like. um creating these problems and usually. associating prizes with those problems. and a lot of those problems are still. open like and and there will be some of. them will be open for like maybe.

a couple hundred years and i think. that's actually an interesting hack for. him to collaborate with future. mathematicians you know his his name. will will keep coming up in you know for. future generations but so tao was. working on one of these problems called. the erdog discrepancy and he published a. blog post on like. about that prop about that problem and. he reached like a dead end and then um. all of a sudden there was this guy from. from germany that wrote like a comment. on his blog post saying okay like.

some of the. so this problem is like a sudoku like. flavor and some of the machinery that. we're using to solve the sudoku could be. used here and that was actually the key. to solve their those discrepancy. problems so the there was a comment on. his blog and i think that that that for. me is an example of like how to do. again going back to collaborative. science online um and the power that it. has but taw is is also like pretty. public about. uh like some of the struggles and of of.

being a a mathematician like and and. even he wrote about some of the. unintended consequences of having. extraordinary ability in a field and. used himself as an example when he was. growing up he was extremely talented in. in mathematics from a young age like. todd was. a person he won an uh medal in like one. of the imo's at the age i think was a. gold medal at the age of 10 or something. like that. and so he mentioned that when he was. growing up like and especially in. college when he was in a class that he.

enjoyed it didn't it just came very. natural for him and he didn't have to. work hard to just ace the class and when. he found that the class was boring like. it didn't work and he barely passed. barely passed some i think in college he. almost failed two classes. and and he was talking about that and. how he brought those studying habits or. like uh in existence of studying habits. when he went to prison princeton for his. phd and in for instance when he you know.

started kind of. delving into more complex problems. and classes he struggled a lot because. he didn't have that. those those habits like it wasn't taking. notes and it was he wasn't studying hard. when he when he faced problems. and he almost failed out of his his phd. he almost failed his phd exam and um. it talks about like having this. conversation with with this advisor and. the advisor pointing out like you're not. this is not working. you might have to get out of the program.

and like how that was a kind of a. turning point for him and um. and like it was super important in his. career so i think tao is also like this. figure that apart from being just an. exceptional mathematician he's also. pretty open about you know what what it. takes to to to be a mathematician and. some of the struggles of these type of. careers and and i think it's that's. super important. in many ways he's a contributor to open. science and open humanity so he's being. an open human. through by communicating uh scott.

aaronson is another in computer science. world who's a very different style very. different style but there's something. about a blog that. is authentic and real and just gives us. a window into the. into the mind and soul of of of these. brilliant folks so it's it's definitely. a gift let me ask you about fermat's. library on twitter. which uh. i mean i don't know how to describe it. people should definitely just follow. from ours library on twitter. i i keep following and unfollowing for.

my library because. because uh it's so. it it gives when i follow it um. leads me on down rabbit holes often that. um. that. um that are very fruitful but. but anyway so the the the posts you do. with the on twitter are just these. beautiful. are things that reveal some beautiful. aspect of mathematics. um is there.

um is there something you could say. about the approach there yeah. and um. maybe. maybe broadly what you find beautiful. about mathematics and then more. specifically how. you convert that into a rigorous process. of revealing that in tweet form that's a. good point i think there's something. about math that you know a lot of the. mathematical content and you know paper. papers are like little proofs. um you know. has.

in a way sort of an infinite half-life. what i mean by that is that if you look. at like euclid's elements it's as valid. today as it was when it was created like. 2 000 years ago and that's not true for. a lot of other scientific fields. um. and so. in regards to twitter i think. there's also a very it's a very undex. underexplored platform from a learning. perspective. i think if you look at content on. twitter it's very easy to consume it's.

very easy to read. um. and especially when you're. trying to explain something you know we. humans get a dopamine hit if we learn. something new. and that's a very very powerful feeling. and that's why you know people go to. classes when you have a really good. professor you know it's it's looking for. those dopamine hits and. and and. and that's something that we try to. explore when we're producing content on.

twitter imagine if we we could. if you would on a line to a restaurant. you could go go to your phone to learn. something new instead of social. going to a. you know social network to just and so. and i think. it's very hard to to sometimes to. kind of provide that feeling because you. need to. sometimes digest content and and put it. in a way you know that it feeds 280. characters um. and and it requires a lot of. sometimes time to do that even though.

it's easy to consume it's hard to make. but once you are able to to provide that. eureka moment to people. like that's very powerful they get that. dopamine hit and like you create this. feedback cycle and people come back for. for more and in twitter compared to like. you know an online course for a book you. have a zero percent dropout so people. will will read the content the content. so that it's it's like it's part of the. creators like the person that is. creating the content if you're able to. actually get that feedback cycle it's.

super super powerful. yeah but some of the stuff is like like. how the heck do you find that and and i. don't know why it's so appealing it uh. like. uh this is from uh what is it. a couple days ago. i'll just read out the number two three. four five six seven eight nine is the. largest prime number with consecutive. increasing digits. i mean. that is so cool that's like some weird.

like glimpse. into some deep universal truth. even though it's just a number. i mean that's like so arbitrary like why. why is it so pleasant that that's a. thing but it is in some way it's almost. like it is a little glimpse at some. much bigger. like um and and i think like especially. if we're talking about science there's. something unique. about you go and with a lot of the. tweets you go sometimes from a state of. not knowing something to knowing. something. and that is very particular to science.

science math physics and that again is. extra extremely addictive and that's. that's how i i i feel about that and um. that's why i think people engage so much. with with our tweets and go into rabbit. holes and then they you know we start. with prime numbers and all of a sudden. you are spending hours reading number. theory. things and you go into wikipedia and you. lose a lot of time there but. well the variety is really interesting. too there's human things there's uh.

there's physics things. there's like numeric things like like i. just mentioned but there's also. more rigorous mathematical things. there's stuff that's tied to the history. of math and the proofs and. this visual there's animations. that are looping animations that are. incredible that reveal something. there's uh. andrew wiles i'm being smart and this is. just me now like. ignoring you guys and just going through. oh yeah we're a bit like math drug. dealers we're just trying to get you.

hooked you know we're trying to give you. that hit and trying to get you hooked. yes some people are brighter than others. but i really believe that most people. can really get. to to quite a good level of mathematics. if they're prepared to deal with these. psychological issues of how to handle. the situation of being stuck yeah yeah. there's some truth to that that's truth. i feel that's like really. it's some truth in terms of research and. also about startups you're they're stuck. a lot of the time. before you you get to a breakthrough and.

and it's difficult to endure that. process of like being stuck and because. you're not trying to to be in that. position um i feel uh yeah that's. yeah most people are broken by the. stuckness or like they're destroy like. uh. i i've i've been very cognizant of the. fact that. more and more social media becomes a. thing. like distractions become a thing that. that moment of being stuck. is uh your mind wants to to go do stuff.

that's unrelated to being stuck and. you should be stuck i'm referring to. small stucknesses. like. you're like trying to design something. and it's a dead end basically little. dead ends. on dead ends and programming dead ends. and trying to think through something. and then your mind wants to like. like. like uh this is the problem with this. like. work-life balance culture is like. take a break like as if taking a break. will solve everything sometimes it.

solves quite a bit but like sometimes. you need to sit in a stuckness and. suffer a little bit and then take a. break. but you you definitely need to be. and like most people quit. from that psychological battle of being. stuck and so success is people who. who who uh persevere through that yeah. yeah and and in the creative process. that's also true i was the other day i. was i think was reading about is this um. what is his name ed sheeran like the. musician yeah was talking a little bit.

about the creative process and using was. using this analogy of a faucet like. where you when you turn on a faucet as. like the dirty water coming out in the. beginning. and you just have to you know keep. trusting that at some point your clean. clean clear water will come out but you. have to endure that process like in the. beginning it's going to be dirty water. and and and just you know. embrace that yeah actually this uh the. entirety of my youtube channel and this. podcast have been following that.

philosophy of dirty water. like i've been you know. i do believe that like you have to get. all the crap out of your system first. and uh sometimes it's it's all. sometimes it's all crappy work. i mean i tend to be very self-critical. but i do. think that quantity leads to quality for. some people it does for my the way my. mind works is like just keep. putting stuff out there keep creating. and uh. the quality will come as opposed to. sitting there waiting.

not doing anything until. the thing seems perfect because the. perfect may never come. but just just on like on on our twitter. like profile i really and sometimes when. you look on some of those tweets they. might seem like pretty. kind of. um you know why is this interesting it's. like so raw uh like it's just a number. but i really believe that especially. with math or physics. it is possible to get everyone to love. math or physics even if you think you. hate it it's it's not a function of the.

student or the person that is on the. other side i think is just purely a. function of like how you explain uh. hidden beauty that they hadn't realized. before. it's not easy but i think it's like a. lot of the times it's on like on the. creator's side to to be able to like. show that beauty to the other person i. think some of that is native to to. humans we just have that curiosity and. you look at small toddlers and babies. and like them trying to figure things. out and there's just something that is.

born with us that we we we want for that. understanding we want to figure out the. world around us and and so. yeah it shouldn't be like uh whether or. not people are going are going to to. enjoy it like. i i i also really believe that everybody. has that capacity to fall in love with. with math and physics. you mentioned startup. what do you think it takes to build a. successful startup yeah that. it's what what louise was saying that um.

you need to in to be able to endure. being stuck and and i think. the best way to put it is that startups. don't have. a linear reward function. right you oftentimes don't get rewarded. for effort and and. in most of our lives we go through. these processes that. do. give you those small rewards for effort. right in school you study hard generally. you'll get a good grade and then you. good you get like good grades ever or.

you get grades every semester and so. you're you're slowly. getting rewarded and pushed in the right. direction. for for startups and startups are not. the only thing that is like this but for. startups it's you know you can put in a. ton of effort into something. that and then get no reward for it right. it's like like sisyphus boulder where. you're pushing that boulder up the. mountain. and and and you get to the top and then. it just rolls all the way back down. and and so that's something that i think.

a lot of people are not equipped to deal. with and can be incredibly demoralizing. especially if that happens more than. than a few times. and so but i think it's absolutely. essential to to power through it because. uh by the nature of startups it's often. times you know you're dealing with with. with non-obvious ideas and things that. there might be contrarian and so you're. gonna you're gonna run into into that a. lot you're gonna do things that are not. gonna work out uh and you need to be.

prepared to deal with that but. but we're not coming out of college. you're you're just not equipped i'm not. sure if there's a way to train people to. deal with those non-linear reward. functions but it's definitely i think. one of the most difficult things to you. know. about doing a startup and also happens. in research sometimes you know we're. talking about the default studies being. stuck you just you know you don't like. you try things you get zero results you. close doors you constantly closing doors.

until you you know find something and um. yeah that is a big thing. what about sort of this point when. you're stuck. there's a kind of decision whether you. if you have a vision. to persist through through with this. direction that you've been going along. or what a lot of startups do or. businesses is pivot. how do you decide whether like. to give up. on a particular flavor of the way you've. imagined the design and to like adjust.

it or completely. like alter it i think that's a core. question for startups that i've asked. myself exactly and like i've never been. able to come up with a great framework. to make those decisions um i think. that's really at the core of. uh yeah out of a lot of the the toughest. questions that. that people that's that started a. company have to deal with um. i think maybe the best framework that i. i.

was able to figure out like when you run. out of ideas you just you know you're. exploring something it's not working you. try it in a different angle you know you. try a different business model yeah when. you run out of ideas like you don't have. any more cards just. switch and yeah. it's not perfect. because you also it's you have a lot of. stories of startups with like. people kept pushing and then you know. that paid off. and then you have uh philosophies.

there's like fail fast and pivot fast um. so it's. you know it's hard to you know balance. these two worlds and understand what is. the best framework. and i mean if you look at four miles. library your. maybe you can correct me but it feels. like you're an operating in a space. where there's a lot of things that are. broken. and or could be significantly improved. so it feels like there's a lot of. possibilities for pivoting. or like how do you revolutionize science.

how do you revolutionize. the aggregation the. the annotation the commenting the. community around information about. knowledge structured knowledge i mean. that's kind of what like stack overflow. and stack exchange has struggled with. to come up with a solution and they've. come up i think with an interesting set. of solutions that are also i think. flawed in some ways but they're much. much better than the alternatives. but there's a lot of other possibilities. if we just look at papers as we talked.

about there's so many possible. revolutions and they're a lot of money. to be potentially made in those. revolutions plus coupled with that the. benefit to humanity. and so like you're sitting there. like i don't know how many people are. legitimately from a business perspective. playing with these ideas it feels like. there's a lot of ideas here true there. is are you right now grinding in a. particular direction like is there a. like a five-year vision that you're. thinking in your mind. for us it's more like a 20-year vision.

in the sense that uh we we've. consciously tried to make the decision. of. so we so we run fermat says it's a side. project and it's a separate in the sense. like it's not what we're working on. full-time. and uh. but. our thesis there is that. we actually think that it's that's a. good thing at least for for this stage. of vermont's library um and also because. some of these projects.

you just. if you're coming from a start from a. startup framework you probably try to. try to fit every single idea into. something that can change the world. within three to five years and there's. just some problems that take longer than. that right and so you know we're talking. about archive and i'm very doubtful that. you could grow. like archive into what it is today like. within two or three years no matter how. much money you throw at it there's just. some things that can take longer but you.

need to be able to power through. the the the time that it takes um but if. you look at it as okay this is a company. this is a startup we have to grow fast. we have to raise money then uh. then sometimes you might forgo those. ideas because of that um because they. don't very well fit into the. the typical. startup framework and so for us formats. it's something that we're okay with. growing with having it grow slowly and. and maybe taking many years and and and.

that's why we think it's it's not a bad. thing that it is a side project because. it makes it much more. um. acceptable in a way and that to to to be. able to be okay with that that said i. think what happens is. if you keep pushing new little features. new little ideas i feel like there's. like certain ideas will just become. viral. like and then you just won't be able to. help yourself but it'll revolutionize. things it feels like there needs to be.

that needs to be but there's um. opportunity for viral ideas to change. science absolutely. and maybe we don't know what those are. yet it might be a very small kind of. thing maybe you don't even know if. should this be a for-profit company. that's the wikipedia question yeah um. is that a lot of questions like really. fundamental questions about this space. that we've we've talked about i mean you. take wikipedia and you try to run it as. a startup and by now we'd have a paywall.

you'd be paying 9.99 a month to to read. more than 24 i mean that's that's one. view yeah the other. the ad driven model so they rejected the. ad driven model. i don't know if we could i mean this is. a difficult question. you know if archive was supported by ads. i don't know if that's bad for archive. if vermont's library was supported by. ads i don't know i don't. i'm not it's not trivial to me i'm. unlike i think a lot of people.

uh i'm not against advertisements i. think as when done well are really good. i think the problem with facebook and. all the social networks are the way. the lack of transparency around the way. they use data. and. the lack of control the users have over. their data and not the fact that data is. being collected and used to sell. advertisements it's a lack of. transparency lack of control if you if. you do a good job of that i feel like. it's really nice way to make stuff free. yeah for example it's like stack. overflow right yeah.

i think they've done an okay a good job. with that even though as we said like. they're capturing very little of the. value that they're putting out there. right but but it makes it a sustainable. company and and they're providing a lot. of it's a fantastic and very productive. community let me ask a. a ridiculous tangent of a question where. he's you wrote a paper on a on game of. thrones battle of winterfell just. as a side little i i'm sorry i noticed. i'm sure you've done a lot of ridiculous. stuff like this i just noticed that.

particular one. by ridiculous i mean you're ridiculously. awesome can you describe the the. approach in this work which i believe is. a legitimate publication. so going back to the original like uh. when we were talking about the backstory. of of papers and the importance of that. so this is actually you know it was. when the last season of the the show was. airing uh this was a during a company. lunch. we there was in in the last season. there's the. there's a really big battle against the.

the forces of evil and the you know. forces of good and this is called the. battle of winterfell. and um. in this battle there are like these two. armies and there's a very particular. thing that they have to take into. account is that in the army of dead like. if someone dies in the army of the. living like that person is gonna you. know be a reborn as. a soldier in the army of the dead yes. and so that was an important thing to.

take into account and the initial. conditions as you specify it's about a. hundred thousand on each side exactly so. i was able i was able to like based on. some images like on previous episodes to. figure out what was the size of the. armies and so what i want what we wanted. to do what we were theorizing was like. how many soldiers does like a a soldier. on the army of the living has to kill. in order for them to be able to this to. destroy the army of the dead without. like. losing because every time.

one of the good soldiers died is going. to turn into like the other side and so. it's so i we we were theorizing that and. and i wrote a couple of uh differential. equations and um i was able to figure. out that based on the size of the armies. i think i think was the ratio had to be. like 1.7 so it had to kill like 1.7 um. soldiers like the army of the dead in. order for them to win the battle. well yeah that's that's science it is. it's it's. most powerful. and this is also somehow a pitch.

for uh like a hiring pitch in a sense. like this is the kind of uh yeah before. the science you do it exactly yeah. well turned out to be you know as as is. for people that have watched these shows. is like they know that every time you. try to predict something that is going. to happen it's going to you're going to. fail miserably and that's what happened. so it was not not at all important. for the show but yeah we ended up like. putting that out and there was a lot of. people that shared that i think was some. like elements of the of the show the.

cast of the show that actually retweeted. that and shared that at first so it was. fun i would love if this kind of. calculation happened uh like during the. making of the show or the you know i. love it. like in um. for example i now know um alex garland. the director of ex machina. and i love it. he doesn't seem to be. some. not many people seem to do this but i. love it when directors. and people who wrote the story. really think through the technical.

details. like whether it's knowing like how. things even if it's science fiction. if you were to try to do this how would. you do this like stephen wolfram and his. son were. were collaborating with the movie. arrival in designing the alien language. how you communicate with aliens like how. would you really have. a math-based language that uh that could. span the alien. and uh being and the human.

being so i i love it when they have that. kind of regular the martian was also big. on that like the book in the movie was. all about like can we actually. is this plausible can these happen it. was all about that and that can really. bring you in like the sometimes the. small details uh i mean the guy that. wrote the martian book is another book. that is also filled with those like. things that when you realize that okay. these are grounded in in science can. just really bring you in yeah right like.

there's a book about a colony on the. colony on the moon and he goes about. like all the details that would you know. be required about setting up a colony in. the moon and like things that he. wouldn't think about like the the fact. that um they would you know it's hard to. bring like uh air to the moon say so. they wouldn't like how do you make that. breathable that environment breathable. you need to bring oxygen but like you. you you probably wouldn't be bring. nitrogen so what you do is like instead. of having a an.

atmosphere that is 100. oxygen you like decrease the pressure so. that you have the same ratio of oxygen. on earth but like lowering the pressure. here and so like things like water boils. at the lower temperature so people would. would have coffee and the coffee would. be colder like there was a problem in. this uh environment in the moon so like. and these are like small things in the. book. but. i studied physics so like when i read. this i that throws me into like.

a tangents and i start researching that. and it's like i really like to read. books and and watch movies when they go. to that level of detail. uh uh about science yeah i think. interstellar was one where they also. consulted heavily with with the number. of yeah i think even resulted in a. couple of papers a couple papers about. like the black hole uh visualizations. and um. yeah but there's and there's even more. examples of interesting science around. like these fantasy. we were reading at some point like these.

guys that were uh trying to figure out. if if the tolkien's middle earth if it. was uh round if it was like a sphere if. it was like. based on the map and some of the. references in the. in the books and so uh yeah we actually. i think we tweeted about that. yeah we did based on the distance. between the cities you can actually. prove that that could be like a map of a. sphere or like a spheroid and and you.

can actually calculate the radius of. that planet. uh. that's fascinating. i mean yeah that's fascinating but. there's something about like calculating. the number. like. exactly the calculation you did for for. the battle winterfell is um. there's something fascinating about that. because it's not like being. that's very mathematical versus like. grounded in physics.

and that's really interesting i mean. that's like injecting mathematics into. fantasy. there's there's something um i see. magical about that and and that for me. that's why i think it's also when you. look at things like. like uh fermat's last theorem like. problems that are very kind of. self-contained and simple to state yeah. i think like. that's the same with that paper it's. very easy to understand the boundaries. of the problem you know. um and and that for me that's why those.

and that's why math is so appealing and. those like problems are also so. appealing to the general public it's not. that they look simple or that people. think that they're easy to like solve. but i feel that a lot of the times they. are. almost intellectually democratic because. everyone. understands the starting point you know. you look at fermat's last theorem. everyone understands like is the this is. the the universe of the problem and the. same maybe with that paper everyone. understands okay these are the starting. conditions. and um.

and and yeah that the fact that it. becomes intellectually democrat and i. think that's a huge motivation. for people and that's why. so so many people gravitate towards. these like riemann hypotheses or. vermont's last theorem or that simple. paper which is like just one page it's. very simple. and i just talked to somebody i don't. know if you know who he is jaco willink. who is uh. this person. who among many things loves military. tactics so. he would probably either publish.

a follow-on paper maybe you guys should. collaborate but he would see the. fundament the basic assumptions that he. started that paper with is flawed. because you know there's like dragons. too right there's like. like you have to integrate tactics. because not it's not it's not a. homogeneous system. it's not you i don't take into account. the dragons and like and he would say. tactics fundamentally change the. dynamics of the system. and so like. that's what happened. so uh yeah so at least from a scientific.

perspective he was right but he never. published so there you go. uh let me ask the most important. question you guys are from. portugal both yeah. so. who is the greatest soccer player. footballer of all time. yeah i think we're a little bit biased. on this topic but uh i mean i have. maradona. i i have a huge i have a you know. tremendous respect for for what um here. we go. this is the political issue. we can convince you i i i mean i have.

tremendous respect for what ronaldo has. achieved in in his career and and i. think soccer is one of those sports. where i think you can get to maybe be. one of the best players in the world. we. if you just have like natural talent and. even if you don't put a lot of hard work. and discipline into soccer you can be. one of the best players in the world and. i think ronaldo is kind of like of. course he's naturally talented but yeah. exactly from portugal um and and not uh.

not the brazilian in this case and so um. and ronaldo put like came from nothing. he he's known from being probably one of. the hardest working athletes in the game. and and i see that sometimes a lot of. these discussions about the best player. a lot of people train tend to gravitate. towards like um you know this person is. naturally talented and the other person. has to work hard and so and so as if it. was bad if he had to work hard to to be. good at something and i think that you.

know the the. i think so many people fall into that. trap and the reason why so many people. fall into that trap is because if you. are saying that someone. is good and achieved a lot of success by. working hard as opposed to achieving. success because it has some sort of. god-given natural talent then you can't. explain why the person was born with. that. what does it tell you about you. it tells you that maybe if you work hard. on a lot of fields you could have. could accomplish a lot of great things.

and i think that's hard to digest for a. lot of people. and and that way ronaldo's inspiring. that i think so you find hard work. that's probably but he's he's way too. good looking that's nice. you know that's the yeah i don't like. him probably no i like the part of the. hard work and like of him being like one. of the hardest working athletes in in. soccer. so he is to you the greatest of all time. is he up there is he would be number one. okay. do you agree with this thing oh hardly. disagree well i definitely disagree i.

mean i i like him very much he works. hard i admire. i admire you know um. would like he's an incredible uh. a goal scorer right. um. but. i. so first of all. leo messi and there was some confusion. because i've kept saying maradona is my. favorite player but i i think. i think leo has surpassed them. so uh. um it's messy that mardonna then.

pele for me but the the reason is is um. there's certain. aesthetic definitions of beauty that i. admire whether it came by hard work or. through god-given talent or through. anything and it doesn't it doesn't. really matter to me there's certain. aesthetic. like genius when i when i see it to me. and uh especially it doesn't have to be. consistent it is in the case of messi in. a case in the ronaldo but just even. moments of genius which is where.

maradona really shines it i. even if that doesn't translate into like. results and goals being scored right. right and that's the challenge like they. did that. because that's where people that tell me. that leo messi's never. even on strong teams have led his. the national team people as part of the. world cup right as really important and. to me no it's the moment like winning to. me was never important.

what's more important is the moments of. genius and. but you're you're talking to the human. story. and. um. yeah cristiano ronaldo definitely has a. beautiful human story yeah and i think. you can't i for me it's hard to decouple. those two um i i don't i don't just look. at you know the the list of achievements. but i like how he got there and how he. keeps pushing the boundaries at like. almost 40 yeah and how that sets up an. example like maybe 10 years ago i. wouldn't have ever imagined that like.

one of the top players in the world. could be a top player at like 37 or but. so and there's an interesting ten the. human story is really important but like. if you look at ronaldo he's like he's. somebody like kids could aspire to be. but at the same time i also like. maradona who like is a as a tragic. figure in many ways it's like the you. know the drugs the the temper all of. those things that's beautiful too like i. don't. necessarily think to me.

the flaws are beautiful too in in. athletes i don't think. you need to be perfect i agree uh from a. personality perspective those flaws. are also beautiful so but yeah there is. something about. hard work. and uh there's also something about the. being an underdog and being able to. carry a team. uh that's that's an argument from. maradona i don't know if you can make. that argument for messi and ronaldo. either because they've all played on.

superstar teams for most of their lives. so i don't know. how it you know it's it's difficult to. know how they would do. um. when they had to work. like did what mardonna had to do to. carry a team on his shoulders true. and pele did as well and so depending on. the the context yeah maybe you could. argue that within portuguese national. team but they were we have a good team. uh yeah but maybe with what maradona did. with you know.

naples and and a couple other teams it's. it seemed incredible this is the beauty. of the game that you know we're talking. about all these different players that. have. or especially you know if you're. comparing messi and ronaldo that have. such different you know styles of play. and also even. their bodies are so different and and. and but. these two. very different players can be at the top. of the game and that's not that's the. they're not a lot of other sports where. you where you have that you know like. you have kind of a mental image of a.

basketball player and like the the top. basketball players kind of fit that. mental image and and they look a certain. way. and um. but for soccer there's so there's. it's it's not so much like that and and. that's i think that's that's beautiful. uh but that's that really adds something. to the sport. well do you play soccer yourself have. you played that in your life what do you. find beautiful about the game yeah i. mean it's one of the i'd say it's the. biggest sport in portugal and so growing.

up we played a lot did you see the paper. from deepmind i didn't look at it where. they're like uh doing some uh analysis. on soccer strategy yeah interesting i. saved that paper uh i haven't read it. yet um it's actually i i when i was in. college i actually did some. research on on applying um. machine learning and statistics in. sports and in our ca in our case we're. doing it for basketball. but uh.

what they're effectively trying to do. was. have you ever watched moneyball like. yeah so they're trying to do something. similar to. taking that in this case basketball. taking a statistical approach to. to to basketball um. the interesting thing there is that. baseball is much more about having these. discrete events that happen kind of in. similar conditions and so it's easier to. take a statistical approach to it. whereas basketball is a much more. dynamic game. it's harder to measure.

um. it's hard to to replicate these. conditions and so. you you have to think about it in a. slightly different way and so we were. doing work on that and working like with. the celtics to analyze the the the data. that they had like they had these. cameras in the in the arena they were. tracking the players and so you so they. have they had a ton of data but they. didn't really know what to do with it. and so we were doing work on that and. and and soccer is maybe an even a step. further it's it's right it's a game. where you don't have as many.

in in basketball you have a lot of field. goals and so you can measure success uh. soccer it's it's right it's more of a. poisson process almost where it's like. you have a goal like or two and again in. terms of metrics i wonder if there's a. way and i've actually have thought about. this in the past never coming up with. any good solution if there's a way to. definitively say whether it's messier. and now they're the greatest of all time. like honestly sort of measure. interesting. like convert the game of soccer into. metrics like you said baseball but like. those moments of genius like pat like um.

you know if it's just about goals or. passes that led to goals that feels like. it doesn't capture the genius of them. yeah they'll be like you know like. like you kind of do you have more. metrics for instance in chess right and. you can try to understand how hard of a. move. there was you know there's like bobby. fischer has this move that like. that it's i think it's called the move. of the century where uh. you have to go so deep into the tree to.

understand that that was the right move. and you can quantify it how hard it was. so it'd be interesting to try to think. of those type of metrics but say yeah. for soccer computer vision unlocks some. of that for us that's that's one. possibility i have a cool idea a. computer vision product likes that you. could build for soccer. i'm taking notes. if you could detect the ball and like. imagine that um this seems like totally. doable right now but like if you could. detect when the ball enters one of the. goals and like just had like um you know.

a crowd cheering for you when you're. playing soccer with your friends every. time you score a goal or you had like. the the champions league song going on. yeah and like having that like you go. play soccer with your friends you just. turn that on and there's like a computer. vision like program analyzes the ball. detects the ball every time there's a. goal like if you miss like there's a you. know the fans are reacting to that and. then. it should be pretty simple by now it's. like i think there's an opportunity. there so yeah just throwing that i would. go all out but by the way i did uh i've.

never released i was thinking of just. putting on github but i did write. exactly that which is the trackers for. the players. uh for the for the bodies of the player. it's this is the hard part actually. the detection of player bodies and the. ball is not hard what's hard is. very like robust tracking through time. of each of those. so like so i wrote a track of this. pretty damn good this is this is that is. that open source. i know i've never released it because. that's interesting because i thought.

like. i need to i would. this is the perfection thing because i. knew it was going to be like. it's going to pull me in and and it. wasn't really that done. and so i've never actually been part of. a github project where it's like really. active development and i didn't want to. make it i knew there's a non-zero. probability that will become my life for. like a half a year. that's uh just how much i love soccer. and all those kinds of things and and. ultimately it will be all for just the.

the joy. of analyzing the game which i'm all for. i remember you also like one of in one. of the episodes you mentioned that you. did also a lot of eye tracking analysis. like joe rogan's that was the that was. the research side of my life interesting. yeah and you have that library right you. you kind of downloaded all the episodes. yep allegedly i and of course i didn't. if you're a lawyer listening to this no. it is i i was listening to the episode. where you mentioned that and i was. actually there was something that i and. i might ask you for for access to that. to allegedly that library uh but i was.

doing some not not regarding like eye. tracking but i was. playing around with um analyzing the. distribution of silences on uh one of. the joe rogan episodes so like i did. that for the elon. conversation where it's like you just. take all the silences. like after joe asked the question and. elon responded and you plot that. distribution and like and see how. how that looks like yeah i think there's. a huge opportunity especially long-form.

podcasts. to do that kind of analysis bigger than. joe exactly but it has to be a fairly. unedited podcasts so that you don't cut. the silence so one of the benefits i. have like doing this podcast is like the. the what we're recording today is. there's. individual audio. being recorded. like i have the raw information no it's. when it's published it's all combined. together and individual video feeds so. even when you're listening which i. usually don't i only show one video. stream. i i'll know i can track your blinks and.

so on. um but yeah but ultimately the hope is. you don't need that raw data because if. you don't need the raw data for whatever. analysis you're doing. you can then do a huge number of. products because there's so it's quickly. growing now the number especially. comedians. there's uh quite a few comedians with. with long-form podcasts. and. they have a lot of facial expressions. they have a lot of fun and all those. kinds of things and it's it's prone for. analysis yeah and it's there's so many.

interesting things that. that that idea actually sparked because. i was watching a. um. a q a by by steve jobs and i think was. at mit and then like people's like he. did a talk there and then. the q and a started and people started. asking questions that i was i was. working while listening to it and like. someone asked the question and he goes. like on a 20-second silence before. answering the question i like i had to. check if the if the video hadn't paused. or something. and and i was thinking about like like.

if that is a feature of a person like. how long on average you take to respond. to a question and if it's like that's. fascinating it has to do with it like. how thoughtful you are and if that. changes over time well but it also could. be this really fascinating metric. because it also could be. it's certainly a feature of a person but. it's also a function of the question. like if you normalize to the person. you can probably infer a bunch of stuff. about the question so it's a nice flag. like it's a really strong signal the. length of that silence.

relative to the usual silence they have. so one the silence is a measure of how. thoughtful they are and two the. particular sounds doesn't measure how. thoughtful the question was thoughtful. the question was it's really interesting. i mean yeah yeah i just analyzed elon's. uh um. episode but i think there's like room. for exploration there i feel like the. average they could do for comedians. would be. like i mean the time would be so small. because you're trained to like i would. think you're reacting to hecklers you're. reacting to all sorts of things you have.

to be like so quick maybe right yeah but. some of the greatest comedians are very. good at sitting in the silence i mean. there there's lucy kaye. they played with that. because you have a rhythm and you like. um. dave chappelle a comedian who did uh. joe's show recently. he has uh. especially when he's just having a. conversation. he does long pauses it's kind of cool. because it uh. it's one of the ways to have people hang.

in your word is to play with the pauses. to play with the silences and the. emphasis. and like mid-sentence there's a bunch of. different things that uh it'd be. interesting to really. really analyze but still soccer to me is. uh that's that that one that's. fascinating just i just want a. conclusive definitive statement about. it's like there are so many. soccer highlights of both messi and. ronaldo. i just feel like the raw data is there.

um because you don't have that with pele. just remember yeah through but here's a. huge amount of high def data then the. the annoying the difficult thing and. this is really hard for tracking and. this is actually where i kind of gave up. because i didn't really give much effort. but i gave up. to the the way that highlights or. usually football match are filmed is. they switch the camera so they'll.

they'll do a different switch. perspective so you have to. it's a really interesting computer. vision problem when the perspective is. switched you still have a lot of overlap. about the players but the perspective is. sufficiently different that you have to. like recompute everything so i. there there's two ways to solve this so. one. is doing it the full way where you're. constantly doing the slam problem you. you're doing a 3d reconstruction the. whole time and projecting into that 3d. world. but you could also there could be some. hex. that i wonder like some trick where you.

can hop. like when the perspective shifts. do a high probability tracking hops from. one object to another but i i thought. especially in exciting moments when when. uh. when you're passing players like you're. doing a single ball dribble. across players and you switch. perspective which is when they often do. when you're making a run on goal if you. switch your perspective. it's it feels like that's going to be.

really tricky to get right. automatically but in that case i feel. like if somebody released that data set. or it's like you just have all like. these this data set a massive data set. of all these games from from say ronaldo. and messi like and just you just add. that in like whatever csv format and. some some publicly available data set. like that i feel like people would just. there there would be so many cool things. that you could do with it and you just. set it free and then like the world. would like do its thing and then like.

interesting things would come out of it. by the way. i have this data set so. the two things that i've did of this. scale. uh is soccer so it's body pose and ball. tracking for soccer and then um i tr. it's. pupil tracking and blink tracking for. it was joe rogan and a few other. podcasts that i did so those are the two. data sets i have. did you analyze any of your podcasts. no i i think i really started doing this. podcast after.

after doing that work and it's difficult. to. maybe i'd be afraid of what i find. i'm already annoyed with my own voice. and video like editing it. but perhaps that's the honest thing to. do because uh one useful thing. about doing computer vision about myself. is like i know what i was thinking at. the time so you can start to like. connect the particular. the behavioral peculiarities of like the.

way you blink the way you squint. the way you. close your eyes like. talking about details there's it's like. for example i just closed my eyes. is that a blink or no. like. figuring that out in terms of timing in. terms of the blink dynamics. is tricky it's very doable i. i think there's universal laws. about what is a blink and what is a. closed eye and all those things plus. makeup and eyelashes i actually um. have annoyingly long eyelashes so i.

remember when i was doing a lot of this. work i i would cut off my eyelashes. when like especially it was funny like. female colleagues were like what the. fuck are you doing like those no keep. the eyelashes but because it got in the. way made the computer vision a lot more. difficult but. super interesting topics yeah but. speaking about the. one uh still on the topic of the data. sets for sports there's one um one paper. that and i actually annotated it on. fermat and uh.

it's it was published in uh 90s 90s i. believe 90s or 80s i forget but they're. you the researcher was effectively. looking at. the hot and phenomena in basketball. right so whether like the fact that you. just made a field goal um if you know if. on your next attempt if you're more. likely to make it or not. um. and it was super interesting because i. mean he pulled like i think 100.

undergrads and. i think from stanford and cornell and. asking people like do you. you think that's that you have a higher. likelihood of making your free throw if. you just just made one and i think it's. like 68 68. said yes they believe that and and then. he looked. at the data. and this was back in as i said like a. few decades ago and so i think he had a. data set of about. he looked at it specifically for free. throws and he had a data set of about 5. 000 free throws.

and. and effectively what he found was that. specifically in the case of free throws. he didn't for the aggregate data he. didn't find um that. he couldn't really spot that correlation. that hot end correlation so if you made. the first one you weren't more likely to. to make the second one what he did find. was that they were just better at the. second one because you just got like. maybe a tiny practice and you just you. attempted once and then and then you're.

going to be better at the next one and. then i i then i went and there's a data. set on kaggle that has like 600 000 free. throws and i reran the the same. computations and and. confirmed like you can see a very clear. pattern that they're just better at. their second free throw um that's. interesting because i think there's. similar. that kind of analysis is so awesome. because i think with tennis they have. like uh like a fault like when you serve. they have analysis of like are you most. likely to miss the second serve if you.

missed first obviously. um yeah i think that's the case so that. integrates. that's so cool when psychology is. converted into metrics in that way and. in sports it's especially cool because. it's such a constrained system that you. can really study human psychology. because it's repeated it's constrained. so many things are controlled which is. something you rarely have in. in the wild psychological experiment so. it's cool. uh plus everyone loves it like sports is.

really cool to analyze. people actually care about the results. yeah um i still think well like i yeah. and i will definitely publish uh this. work on messi versus ronaldo and i'd. love to read it objective fully. objective to peer review. um yeah this is very true this is not. past peer review. um let me ask sort of um. an advice question. to uh to young folks. you've explored a lot of fascinating.

ideas in your life. you've built a startup. worked on physics worked in computer. science. what advice would you give to young. people today in high school maybe early. college about life about career. about science and mathematics. i remember like i. i read like i remember reading that um. ponkario was once asked by um. a french journal about his advice for. young people and what was his teaching.

philosophy and he said that like one of. the most important things that parents. should teach their kids is how to be. enthusiastic. um. in regards to like the mysteries of the. world. and that he said like striking that. balance was actually one of the most. important things between like in. education you know you want to. have your kids be enthusiastic about the. mysteries of the world but you also. don't want to traumatize them like if. you really force them into something and. i think like especially. if you're young i think you.

you should be curious and i think you. should ex. explore that curiosity to the fullest to. the point where you even become almost. as an expert on that topic. and now and. you might start with something that it's. small like you might start with you know. you're interested in numbers and how to. factor numbers into primes and then all. of a sudden you go and and you're like. lost in number theory and you discover. cryptography and then all of a sudden. you're buying bitcoin. and i and i think you should do these um.

you should really try to fulfill this. curiosity and you should live in a. society that allows you to fulfill this. curiosity which is also important and i. think you should do these not to get to. some sort of status or fame or money but. i think this is the way this iterative. process i think this is the way to find. happiness. and. and i think this is also allows you to. find the meaning for your life. i think it's all about like being. curious and being able to fulfill that. curiosity and that path.

to fulfilling that uh your curiosity. yeah the the the start small and let the. fire build is kind of interesting way to. think about it and you never know where. you're gonna end up it's it's. like for instance from us it's just a. really good example we started like just. by doing this as an internal like thing. that we did with in the company and then. we started putting out there and now a. lot of people follow it and know about. it and so um and you still don't know. where females libra is going to end up. actually true exactly so um yeah i think.

that would be my. piece of advice with very limited. experience of course but yeah yeah i. agree i agree. uh i mean is there something in from. particular. journal from the computer science versus. physics perspective. uh do do you regret not doing physics do. you regret not doing computer science. which one is the the wiser the better. human being this is messy versus ronaldo. those are very. i i don't know if you would agree but.

they're kind of different disciplines. true yeah. very much so. um i actually actually uh. i was i i had that question in my mind i. i took physics classes uh as an. undergrad uh or like. besides what i had to take. and um. it's definitely something that i. considered at some point. um. and. and that that i. i i do feel like later in life that.

might be something that. i'm not sure if regret is. is the right word but it's it's kind of. something that i can imagine in an. alternative universe what would have. happened if i if i've gone into physics. um. i try to think that like well depends on. what your. path ends up being but that it's it's. not. super important right like exactly what. you decide to. major on like i think there's there's. um. i think tim urban like the blogger had a.

good visualization of this where it's. like you know like he. he has a picture where you have all. sorts of paths that he could pursue in. your life and then maybe you're in the. middle of it and so there's maybe some. paths that are not accessible to you but. like the tree that is still in front of. you. gives you a lot of optionality and so um. there's two lessons to learn from that. like we have a huge number of options. now. and probably you're just one. to reflect. like to try to uh derive wisdom from the.

one little path you've taken so far may. be flawed because there's all these. other paths you could have taken yeah so. it's like. uh so one it's inspiring that you can. take any path now and two. it's like you you the path you've taken. so far is just one of many possible ones. but it does seem that like. physics and computer science both open a. lot of doors in a lot of different doors. it's very interesting it is i i like in. this case like and especially in in our.

case because i could see the difference. i studied i. i did i went to college in europe and uh. went to college here in the us so i. could see the differences like in the. european system is. um more rigid in the sense that when you. decide to study physics you don't have a. lot especially in the early years you. don't have a lot of um you can't choose. to take like a class from like computer. science course or something like that. you don't have a lot of freedom to. explore in that sense in university as. opposed to here in the us where you have. more freedom and i think um.

i think that's important i think that's. what constitutes you know a good kind of. educational system is one that. gravitates towards the interests of a. student as as you progress but i think. in order for you to do that you need to. explore different areas and i i felt. like if i had a chance to take say more. computer science class when i was in. college i would have probably. have taken those classes but um yeah but. i ended up like focusing maybe too. too much in physics and i think you're. at least. my perception is that you can explore.

more more. fields but there is a kind of it's funny. but physics can be difficult. so i don't see too many computer science. people than. exploring into physics it's only like. the one. the not the one but one of the. beneficial things of physics it feels. like it. uh. what was it rutherford that said like. like basically that physics is the hard. thing and everything is easy uh so like.

there's a certain sense once you've. figured out some basic like physics. that it's not that you need the tools of. physics to understand the other. disciplines it's that you're empowered. by having done difficult shit i mean the. ultimate i think is probably mathematics. there yeah true. uh so maybe just doing difficult things. and proving to yourself that you can do. difficult things whatever those are. that's not positive i believe not. positive yeah and i think like i i. before i started a company i had like i. worked in. the financial sector for a bit and like.

i think having a physics background i. was i felt i was not afraid of like. learning like finance things and i think. like when you come from those. backgrounds you are generally not afraid. of stepping into other fields and. learning about those because. um yeah i feel they've learned a lot of. difficult things and um. yeah that's an added benefit i believe. this was an incredible conversation luis. joao. we started with uh who do we start with.

feynman ended up with messi and ronaldo. so this is like the perfect conversation. it's really an honor that you guys would. waste all this time with me today it's. it was really fun thanks thank you so. much for having us yeah thank you so. much. thanks for listening to this. conversation with louise and joe. albertalla and thank you to skiff simply. safe indeed netsuite and for sigmatic. check them out in the description to. support this podcast. and now let me leave you with some words. from richard feynman nobody ever figures.

out what life is all about. and it doesn't matter explore the world. nearly everything is really interesting. if you go into it deeply enough. thank you for listening i hope to see. you next time. you.